HotSpotter: Using a computer-driven photo-id application to identify sea turtles
Photo identification (PID) in animal studies has been a widely used method for identifying individuals of many species based on unique natural markings and patterns. The use of PID has facilitated investigations in which residency, home ranges, and growth rates have been assessed. However, many PID...
Uloženo v:
| Vydáno v: | Journal of experimental marine biology and ecology Ročník 535; s. 151490 |
|---|---|
| Hlavní autoři: | , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.02.2021
|
| Témata: | |
| ISSN: | 0022-0981, 1879-1697 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Photo identification (PID) in animal studies has been a widely used method for identifying individuals of many species based on unique natural markings and patterns. The use of PID has facilitated investigations in which residency, home ranges, and growth rates have been assessed. However, many PID studies in the past have relied heavily on manual photo matching. More recently, computer-assisted PID programs have been used to identify individuals of different sea turtle species, and reduced time investment in identifying individuals within specific populations. Still, some computer-based PID programs require significant time investment in ensuring photos are captured at consistent angles and lighting conditions, pre-processing image manipulations, and post-processing manual matching confirmation of potential matches provided by the program. For PID to be an effective time and money saving mechanism for wildlife research and conservation, these common drawbacks need to be addressed with a computer-assisted PID program that reduces manipulation and time investment burden, and consistently provides accurate and reliable results. In this study, we evaluated the accuracy of matching individual face images using the HotSpotter (HS) PID program by building a database of 2136 images of hawksbill (Eretmochelys imbricata) turtles, then querying the database with 158 new images to find matches for individual turtles. Overall, we found that with almost no pre-processing manipulation, and with images from highly variable underwater conditions, qualities, and angles, HS correctly matched individuals in the first choice 80% of the time, increasing to 91% in the first six choices. When assessing in-water images only, accuracy for matching increased from 84% in the first choice, to 94% by the sixth choice. We suggest that the integration of HS technology into a global, web-based PID system will increase the ability to remotely identify individual marine organisms on a global scale, and improve usability for community scientists who may have little to no technical training.
•Use of HotSpotter automated computer photo-ID system.•HotSpotter requires essentially no pre/post manipulations.•HotSpootter able to match wide range of images with quality and angle variances.•High levels of accuracy of photo identification in sea turtles.•Potential for photo-ID system use in other marine taxa. |
|---|---|
| AbstractList | Photo identification (PID) in animal studies has been a widely used method for identifying individuals of many species based on unique natural markings and patterns. The use of PID has facilitated investigations in which residency, home ranges, and growth rates have been assessed. However, many PID studies in the past have relied heavily on manual photo matching. More recently, computer-assisted PID programs have been used to identify individuals of different sea turtle species, and reduced time investment in identifying individuals within specific populations. Still, some computer-based PID programs require significant time investment in ensuring photos are captured at consistent angles and lighting conditions, pre-processing image manipulations, and post-processing manual matching confirmation of potential matches provided by the program. For PID to be an effective time and money saving mechanism for wildlife research and conservation, these common drawbacks need to be addressed with a computer-assisted PID program that reduces manipulation and time investment burden, and consistently provides accurate and reliable results. In this study, we evaluated the accuracy of matching individual face images using the HotSpotter (HS) PID program by building a database of 2136 images of hawksbill (Eretmochelys imbricata) turtles, then querying the database with 158 new images to find matches for individual turtles. Overall, we found that with almost no pre-processing manipulation, and with images from highly variable underwater conditions, qualities, and angles, HS correctly matched individuals in the first choice 80% of the time, increasing to 91% in the first six choices. When assessing in-water images only, accuracy for matching increased from 84% in the first choice, to 94% by the sixth choice. We suggest that the integration of HS technology into a global, web-based PID system will increase the ability to remotely identify individual marine organisms on a global scale, and improve usability for community scientists who may have little to no technical training. Photo identification (PID) in animal studies has been a widely used method for identifying individuals of many species based on unique natural markings and patterns. The use of PID has facilitated investigations in which residency, home ranges, and growth rates have been assessed. However, many PID studies in the past have relied heavily on manual photo matching. More recently, computer-assisted PID programs have been used to identify individuals of different sea turtle species, and reduced time investment in identifying individuals within specific populations. Still, some computer-based PID programs require significant time investment in ensuring photos are captured at consistent angles and lighting conditions, pre-processing image manipulations, and post-processing manual matching confirmation of potential matches provided by the program. For PID to be an effective time and money saving mechanism for wildlife research and conservation, these common drawbacks need to be addressed with a computer-assisted PID program that reduces manipulation and time investment burden, and consistently provides accurate and reliable results. In this study, we evaluated the accuracy of matching individual face images using the HotSpotter (HS) PID program by building a database of 2136 images of hawksbill (Eretmochelys imbricata) turtles, then querying the database with 158 new images to find matches for individual turtles. Overall, we found that with almost no pre-processing manipulation, and with images from highly variable underwater conditions, qualities, and angles, HS correctly matched individuals in the first choice 80% of the time, increasing to 91% in the first six choices. When assessing in-water images only, accuracy for matching increased from 84% in the first choice, to 94% by the sixth choice. We suggest that the integration of HS technology into a global, web-based PID system will increase the ability to remotely identify individual marine organisms on a global scale, and improve usability for community scientists who may have little to no technical training. •Use of HotSpotter automated computer photo-ID system.•HotSpotter requires essentially no pre/post manipulations.•HotSpootter able to match wide range of images with quality and angle variances.•High levels of accuracy of photo identification in sea turtles.•Potential for photo-ID system use in other marine taxa. |
| ArticleNumber | 151490 |
| Author | Safi, Shahnaj Kingen, Colin Hayes, Christian T. Dunbar, Stephen G. Holmberg, Jason Salinas, Lidia Baumbach, Dustin S. Anger, Edward C. Parham, Jason R. Wright, Marsha K. |
| Author_xml | – sequence: 1 givenname: Stephen G. surname: Dunbar fullname: Dunbar, Stephen G. email: sdunbar@llu.edu organization: Marine Research Group, Department of Earth and Biological Sciences, Loma Linda University, Loma Linda, CA 92350, United States of America – sequence: 2 givenname: Edward C. surname: Anger fullname: Anger, Edward C. organization: ScubaTed, Roatán, Honduras – sequence: 3 givenname: Jason R. surname: Parham fullname: Parham, Jason R. organization: WildMe, Portland, OR 97217, United States of America – sequence: 4 givenname: Colin surname: Kingen fullname: Kingen, Colin organization: WildMe, Portland, OR 97217, United States of America – sequence: 5 givenname: Marsha K. surname: Wright fullname: Wright, Marsha K. organization: Marine Research Group, Department of Earth and Biological Sciences, Loma Linda University, Loma Linda, CA 92350, United States of America – sequence: 6 givenname: Christian T. surname: Hayes fullname: Hayes, Christian T. organization: Marine Research Group, Department of Earth and Biological Sciences, Loma Linda University, Loma Linda, CA 92350, United States of America – sequence: 7 givenname: Shahnaj surname: Safi fullname: Safi, Shahnaj organization: School of Public Health, Loma Linda University, Loma Linda, CA 92350, United States of America – sequence: 8 givenname: Jason surname: Holmberg fullname: Holmberg, Jason organization: WildMe, Portland, OR 97217, United States of America – sequence: 9 givenname: Lidia surname: Salinas fullname: Salinas, Lidia organization: Protective Turtle Ecology Center for Training, Outreach, Research Inc. (ProTECTOR, Inc.), Loma Linda, CA 92350, United States of America – sequence: 10 givenname: Dustin S. surname: Baumbach fullname: Baumbach, Dustin S. organization: Marine Research Group, Department of Earth and Biological Sciences, Loma Linda University, Loma Linda, CA 92350, United States of America |
| BookMark | eNqFkMFKAzEURYNUsK1-gZss3UzNmziTjOBCRK0gKGjXIZN50ZTpZEzSQv_eaevKha4eXO658M6EjDrfISHnwGbAoLxczpa4qnGWs3xICriq2BEZgxRVBmUlRmTMWJ5nrJJwQiYxLhljUOTlmLzOfXrrfUoYrukiuu6Damr8ql8PSdYEt8GO9p8--cw1VPd964xOznc0eeoa7JKzWxpR07QOqcV4So6tbiOe_dwpWTzcv9_Ns-eXx6e72-fMcF6mrK4bidzWIhdaNJoDSFlKWRlgUpqiQAkSgdvcCNtYy2shGNi6wqEouDF8Si4Ou33wX2uMSa1cNNi2ukO_jiovCqhAFoIN1epQNcHHGNAq49L-iRS0axUwtbOolmpvUe0sqoPFgeW_2D64lQ7bf6ibA4WDgY3DoKJx2BlsXECTVOPdn_w33rKPTg |
| CitedBy_id | crossref_primary_10_3390_ani13020279 crossref_primary_10_58803_fahn_v4i2_75 crossref_primary_10_1093_jmammal_gyaf048 crossref_primary_10_3897_BDJ_10_e90196 crossref_primary_10_1002_ece3_10260 crossref_primary_10_1038_s41598_024_68302_0 crossref_primary_10_1002_ece3_71167 crossref_primary_10_1007_s00227_023_04226_z crossref_primary_10_1016_j_ecoinf_2022_101874 crossref_primary_10_1016_j_jembe_2023_151923 crossref_primary_10_3390_jmse11050889 crossref_primary_10_36253_a_h_15519 crossref_primary_10_3389_fmars_2024_1362703 crossref_primary_10_1111_maec_12696 crossref_primary_10_1007_s42991_022_00224_8 crossref_primary_10_1007_s42991_022_00229_3 crossref_primary_10_1016_j_ecoinf_2025_103158 crossref_primary_10_1016_j_jembe_2021_151632 crossref_primary_10_1515_mammalia_2023_0071 crossref_primary_10_3389_fmars_2021_671061 crossref_primary_10_1111_csp2_70127 crossref_primary_10_1898_NWN22_12 crossref_primary_10_3389_fevo_2022_983260 crossref_primary_10_3390_mps7010002 crossref_primary_10_2744_CCB_1650_1 crossref_primary_10_3389_famrs_2025_1540089 crossref_primary_10_1038_s41598_021_02506_6 |
| Cites_doi | 10.1016/j.jembe.2008.04.005 10.1111/j.1469-7998.2007.00340.x 10.1111/jfb.12857 10.1016/j.jembe.2013.12.010 10.2744/CCB-1355.1 10.1016/j.jembe.2015.12.003 10.1890/07-0315.1 10.3354/meps12483 10.1371/journal.pone.0055935 10.1371/journal.pone.0066035 10.1651/S-2773.1 10.1155/2012/317568 10.1644/08-MAMM-A-328.1 10.3354/esr00113 10.3354/esr00637 10.1111/j.1095-8649.2011.02966.x 10.1016/j.jembe.2015.03.003 10.1111/j.1748-7692.2000.tb00929.x 10.1371/journal.pone.0096992 10.1023/B:VISI.0000029664.99615.94 10.1002/ecy.3027 10.3354/esr00186 10.1651/S-2771.1 10.1016/j.fishres.2006.11.026 10.30906/1026-2296-2018-25-4-311-321 10.3354/ab00215 10.1163/017353710X521546 10.1080/09669582.2016.1174246 10.1579/0044-7447-34.8.628 10.1644/1545-1542(2001)082<0440:CAPMIS>2.0.CO;2 10.1017/S0952836901000516 10.1890/12-1613.1 10.2981/wlb.00023 10.1038/ncomms5117 10.1644/09-MAMM-A-425.1 |
| ContentType | Journal Article |
| Copyright | 2020 Elsevier B.V. |
| Copyright_xml | – notice: 2020 Elsevier B.V. |
| DBID | AAYXX CITATION 7S9 L.6 |
| DOI | 10.1016/j.jembe.2020.151490 |
| DatabaseName | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology Ecology Oceanography |
| EISSN | 1879-1697 |
| ExternalDocumentID | 10_1016_j_jembe_2020_151490 S0022098120301738 |
| GroupedDBID | --K --M -~X .~1 0R~ 1B1 1RT 1~. 1~5 29K 4.4 457 4G. 5GY 5VS 6TJ 7-5 71M 8P~ 9JM AABNK AABVA AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALCJ AALRI AAOAW AAQFI AAQXK AATLK AAXUO AAYJJ ABFNM ABFYP ABGRD ABJNI ABLST ABMAC ABPPZ ABTAH ABXDB ABYKQ ACDAQ ACGFS ACIUM ACRLP ADBBV ADEZE ADMUD ADQTV AEBSH AEKER AENEX AEQOU AETEA AFFNX AFKWA AFMIJ AFTJW AFXIZ AGHFR AGUBO AGYEJ AHEUO AHHHB AIEXJ AIKHN AITUG AJBFU AJOXV AKIFW ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG AVWKF AXJTR AZFZN BKOJK BLECG BLXMC CBWCG CS3 D-I DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FA8 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA HLV HMA HMC HVGLF HZ~ IHE J1W K-O KCYFY KOM LW9 LY3 LY9 M41 MO0 MVM N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SAB SCC SCU SDF SDG SDP SEN SEP SES SEW SPCBC SSA SSJ SSZ T5K TN5 UQL WUQ XPP YQT ZKB ZMT ZY4 ~02 ~G- 9DU AAHBH AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEGFY AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD 7S9 L.6 |
| ID | FETCH-LOGICAL-c336t-bbd8e3fb727a7da311886889c1088c55e818e13f2c7fdff3b7701fb9e11873cc3 |
| ISICitedReferencesCount | 36 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000602892800004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0022-0981 |
| IngestDate | Sun Sep 28 10:15:10 EDT 2025 Tue Nov 18 22:21:01 EST 2025 Sat Nov 29 07:03:34 EST 2025 Fri Feb 23 02:48:01 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Photo identification Sea turtle database management Computer-automated algorithms Marine turtles |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c336t-bbd8e3fb727a7da311886889c1088c55e818e13f2c7fdff3b7701fb9e11873cc3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| PQID | 2551918570 |
| PQPubID | 24069 |
| ParticipantIDs | proquest_miscellaneous_2551918570 crossref_citationtrail_10_1016_j_jembe_2020_151490 crossref_primary_10_1016_j_jembe_2020_151490 elsevier_sciencedirect_doi_10_1016_j_jembe_2020_151490 |
| PublicationCentury | 2000 |
| PublicationDate | February 2021 2021-02-00 20210201 |
| PublicationDateYYYYMMDD | 2021-02-01 |
| PublicationDate_xml | – month: 02 year: 2021 text: February 2021 |
| PublicationDecade | 2020 |
| PublicationTitle | Journal of experimental marine biology and ecology |
| PublicationYear | 2021 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Crall, Stewart, Berger-Wolf, Rubenstein, Sundaresan (bb0065) 2013 Chassagneux, Jean, Bourjea, Ciccione (bb0050) 2013; 137 Dunbar, Ito, K, Dehom, Salinas (bb0085) 2014; 26 Valdés, Ricardo, Trelles, Abad (bb0290) 2014; 32 Hayes, Baumbach, Juma, Dunbar (bb0120) 2017; 25 Calmanovici, Waayers, Reisser, Clifton, Proietti (bb0035) 2018; 589 Martin-Smith (bb0185) 2011; 78 Vaissi, Farassat, Akmali, Sharifi (bb0285) 2018; 25 Chaves, Hall, Feitosa, Côté (bb0055) 2016; 88 Chew, Liew, Joseph (bb0060) 2015; 146 Sreekar, Purushotham, Saini, Rao, Pelletier, Chaplod (bb0260) 2013; 8 Raj (bb0220) 1998; 10 Holmberg, Norman, Arzoumanian (bb0130) 2009; 7 Schofield, Klaassen, Papafitsoros, Lilley, Katselidis, Hays (bb0255) 2020; 101 Lowe (bb0180) 2004; 60 Carter, Bell, Miller, Gash (bb0045) 2014; 452 Den Hartog, Reijns (bb0070) 2014 Rubenstein, Parham, Stewart, Berger-Wolf, Holmberg, Crall, Mackey, Funnel, Cockerill, Davidson, Mate, Nzomo, Warungu, Martins, Ontita, Omulupi, Weston, Anyona, Chege, Kimiti, Tombak, Gersick, Rubenstein (bb0240) 2018 Anderson, Da Vitoria Lobo, Roth, Waterman (bb0010) 2010; 91 Baumbach, Anger, Collado, Dunbar (bb0020) 2019; 18 Anderson, Roth, Waterman (bb0005) 2007; 273 R Core Team (bb0215) 2018 Jean, Ciccione, Talma, Ballorain, Bourjea (bb0135) 2010; 11 Reisser, Proietti, Kinas, Sazima (bb0225) 2008; 5 Gallardo-Escarate, Goldstein-Vasquez, Thiel (bb0100) 2007; 27 Leslie, Hof, Amoraocho, Berger-Wolf, Holmberg, Stewart, Dunbar, Jean (bb0160) 2015; 11 McDonald, Dutton (bb0200) 1996; 2 Dunbar, Salinas, Stevenson (bb0080) 2008; 121 Berger-Wolf, Rubenstein, Stewart, Holmberg, Parham, Menon, Crall, Van Oast, Kiciman, Joppa (bb0025) 2017 Steinmetz, Webster, Rowat, Bluemel (bb0265) 2018; 155 Jewell, Alibhai, Law (bb0140) 2001; 254 Holmberg, Norman, Arzoumanian (bb0125) 2008; 18 Dunbar, Ito (bb0075) 2015; 10 Graham, Roberts (bb0115) 2007; 84 Van Horn, Zug, LaCombe, Velez-Liendo, Paisley (bb0295) 2014; 20 Kelly (bb0150) 2001; 82 Carpentier, Jean, Barret, Chassagneux, Ciccione (bb0040) 2016; 476 Stoddard, Kilner, Town (bb0270) 2014; 5 Gardiner, Doran, Strickland, Carpenter-Bundhoo, Frère (bb0105) 2014; 9 Sacchi, Scali, Pellitteri-Rosa, Pupin, Gentilli, Tettamanti, Cavigioli, Racina, Maiocchi, Galeotti, Fasola (bb0245) 2010; 31 Long (bb0170) 2016; 150 Blackmer, Anderson, Weinrich (bb0030) 2000; 16 McClintock, Conn, Alonso, Crooks (bb0195) 2013; 94 Schofield, Katselidis, Dimopoulos, Pantis (bb0250) 2008; 360 Karlsson, Hiby, Lundberg, Jüssi, Jüssi, Helander (bb0145) 2005; 34 Su, Huang, Cheng (bb0275) 2015; 467 Towner, Wcisel, Reisinger, Edwards, Jewell (bb0280) 2013; 8 Riley, Hale, Harman, Rees (bb0235) 2010; 8 Dunbar, Baumbach, Wright, Hayes, Holmberg, Crall, Berger-Wolf, Stewart (bb0090) 2017 Baumbach, Dunbar (bb0015) 2017; 152 Long, Azmi (bb0175) 2017; 12 Lloyd, Maldanado, Stafford (bb0165) 2012; 2012 McCann, Lowe (bb0190) 2012 Gosselin, Sainte-Marie, Sevigny (bb0110) 2007; 27 Pauwels, de Zeeuw, Bounantony (bb0210) 2008 Richardson, Herbst, Bennett, Bennett (bb0230) 2000 Knox, Cree, Seddon (bb0155) 2013; 37 Frasier, Hamilton, Brown, Kraus, White (bb0095) 2009; 90 Parham, Crall, Rubenstein, Holmberg, Berger-Wolf, Stewart (bb0205) 2018 Lowe (10.1016/j.jembe.2020.151490_bb0180) 2004; 60 Blackmer (10.1016/j.jembe.2020.151490_bb0030) 2000; 16 Chassagneux (10.1016/j.jembe.2020.151490_bb0050) 2013; 137 Schofield (10.1016/j.jembe.2020.151490_bb0250) 2008; 360 Dunbar (10.1016/j.jembe.2020.151490_bb0085) 2014; 26 Towner (10.1016/j.jembe.2020.151490_bb0280) 2013; 8 Crall (10.1016/j.jembe.2020.151490_bb0065) 2013 McDonald (10.1016/j.jembe.2020.151490_bb0200) 1996; 2 Vaissi (10.1016/j.jembe.2020.151490_bb0285) 2018; 25 Parham (10.1016/j.jembe.2020.151490_bb0205) 2018 Carter (10.1016/j.jembe.2020.151490_bb0045) 2014; 452 Knox (10.1016/j.jembe.2020.151490_bb0155) 2013; 37 Lloyd (10.1016/j.jembe.2020.151490_bb0165) 2012; 2012 Baumbach (10.1016/j.jembe.2020.151490_bb0015) 2017; 152 Van Horn (10.1016/j.jembe.2020.151490_bb0295) 2014; 20 Su (10.1016/j.jembe.2020.151490_bb0275) 2015; 467 Rubenstein (10.1016/j.jembe.2020.151490_bb0240) 2018 Kelly (10.1016/j.jembe.2020.151490_bb0150) 2001; 82 Berger-Wolf (10.1016/j.jembe.2020.151490_bb0025) 2017 Gosselin (10.1016/j.jembe.2020.151490_bb0110) 2007; 27 Carpentier (10.1016/j.jembe.2020.151490_bb0040) 2016; 476 Hayes (10.1016/j.jembe.2020.151490_bb0120) 2017; 25 Stoddard (10.1016/j.jembe.2020.151490_bb0270) 2014; 5 Jean (10.1016/j.jembe.2020.151490_bb0135) 2010; 11 Gallardo-Escarate (10.1016/j.jembe.2020.151490_bb0100) 2007; 27 Holmberg (10.1016/j.jembe.2020.151490_bb0130) 2009; 7 R Core Team (10.1016/j.jembe.2020.151490_bb0215) 2018 Gardiner (10.1016/j.jembe.2020.151490_bb0105) 2014; 9 McCann (10.1016/j.jembe.2020.151490_bb0190) 2012 Jewell (10.1016/j.jembe.2020.151490_bb0140) 2001; 254 Karlsson (10.1016/j.jembe.2020.151490_bb0145) 2005; 34 Pauwels (10.1016/j.jembe.2020.151490_bb0210) 2008 Steinmetz (10.1016/j.jembe.2020.151490_bb0265) 2018; 155 Anderson (10.1016/j.jembe.2020.151490_bb0005) 2007; 273 Leslie (10.1016/j.jembe.2020.151490_bb0160) 2015; 11 Anderson (10.1016/j.jembe.2020.151490_bb0010) 2010; 91 Calmanovici (10.1016/j.jembe.2020.151490_bb0035) 2018; 589 Baumbach (10.1016/j.jembe.2020.151490_bb0020) 2019; 18 Chaves (10.1016/j.jembe.2020.151490_bb0055) 2016; 88 Den Hartog (10.1016/j.jembe.2020.151490_bb0070) Reisser (10.1016/j.jembe.2020.151490_bb0225) 2008; 5 Dunbar (10.1016/j.jembe.2020.151490_bb0090) 2017 Richardson (10.1016/j.jembe.2020.151490_bb0230) 2000 Sreekar (10.1016/j.jembe.2020.151490_bb0260) 2013; 8 Frasier (10.1016/j.jembe.2020.151490_bb0095) 2009; 90 Riley (10.1016/j.jembe.2020.151490_bb0235) 2010; 8 Martin-Smith (10.1016/j.jembe.2020.151490_bb0185) 2011; 78 Valdés (10.1016/j.jembe.2020.151490_bb0290) 2014; 32 Graham (10.1016/j.jembe.2020.151490_bb0115) 2007; 84 Dunbar (10.1016/j.jembe.2020.151490_bb0080) 2008; 121 Long (10.1016/j.jembe.2020.151490_bb0170) 2016; 150 Long (10.1016/j.jembe.2020.151490_bb0175) 2017; 12 Holmberg (10.1016/j.jembe.2020.151490_bb0125) 2008; 18 Dunbar (10.1016/j.jembe.2020.151490_bb0075) 2015; 10 Chew (10.1016/j.jembe.2020.151490_bb0060) 2015; 146 Schofield (10.1016/j.jembe.2020.151490_bb0255) 2020; 101 Raj (10.1016/j.jembe.2020.151490_bb0220) 1998; 10 McClintock (10.1016/j.jembe.2020.151490_bb0195) 2013; 94 Sacchi (10.1016/j.jembe.2020.151490_bb0245) 2010; 31 |
| References_xml | – volume: 31 start-page: 489 year: 2010 end-page: 502 ident: bb0245 article-title: Photographic identification in reptiles: a matter of scales publication-title: Amphib.-Reptil. – volume: 88 start-page: 800 year: 2016 end-page: 804 ident: bb0055 article-title: Photo-identification as a simple tool for studying invasive lionfish publication-title: J. Fish Biol. – volume: 32 start-page: 43 year: 2014 end-page: 51 ident: bb0290 article-title: First assay of photo-identification in marine turtles' nesting population publication-title: Rev. Investig. Mar. – volume: 254 start-page: 1 year: 2001 end-page: 16 ident: bb0140 article-title: Censusing and monitoring black rhino ( publication-title: J. Zool. – volume: 146 start-page: 1 year: 2015 end-page: 6 ident: bb0060 article-title: Photographic identification of green turtles ( publication-title: Mar. Turt. Newsl. – volume: 18 start-page: 222 year: 2008 end-page: 233 ident: bb0125 article-title: Robust, comparable population metrics through collaborative photo-monitoring of whale sharks publication-title: Ecol. Appl. – start-page: 1 year: 2018 end-page: 9 ident: bb0205 article-title: An animal detection pipeline for identification publication-title: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), California – volume: 273 start-page: 333 year: 2007 end-page: 339 ident: bb0005 article-title: Can whisker spot patterns be used to identify individual polar bears? publication-title: J. Zool. – volume: 34 start-page: 628 year: 2005 end-page: 634 ident: bb0145 article-title: Photo-identification, site fidelity, and movement of female gray seals ( publication-title: AMBIO – volume: 25 start-page: 311 year: 2018 end-page: 321 ident: bb0285 article-title: Consistency of coloriation pattern and applicability of photo identification method as a tool to identify Kaiser's mountain newt, publication-title: Russ. J. Herpetol. – volume: 2012 start-page: 1 year: 2012 end-page: 7 ident: bb0165 article-title: Methods of developing user-friendly keys to identify Green Sea turtles ( publication-title: Int. J. Zool. – volume: 150 start-page: 4 year: 2016 end-page: 6 ident: bb0170 article-title: Identification of a dead green turtle ( publication-title: Mar. Turt. Newsl. – start-page: 230 year: 2013 end-page: 237 ident: bb0065 article-title: HotSpotter – Patterned species instance recognition publication-title: 2013 IEEE Workshop on Applications of Computer Vision (WACV), Florida – volume: 137 start-page: 1 year: 2013 end-page: 5 ident: bb0050 article-title: Unraveling behavioral patterns of foraging hawksbill and green turtles using photo-identification publication-title: Mar. Turt. Newsl. – volume: 25 start-page: 1 year: 2017 end-page: 17 ident: bb0120 article-title: Impacts of recreational diving on hawksbill sea turtle ( publication-title: J. Sustain. Tour. – volume: 11 start-page: 8 year: 2010 end-page: 13 ident: bb0135 article-title: Photo-identification method for green and hawksbill turtles - first results from Reunion publication-title: Indian Ocean Turtle Newsl. – volume: 10 start-page: 29 year: 1998 end-page: 31 ident: bb0220 article-title: Photo-identification of publication-title: SPC Beche-de mer Inf. Bull. – volume: 12 start-page: 350 year: 2017 end-page: 366 ident: bb0175 article-title: Using photographic identification to monitor sea turtle populations at Perhentian Islands Marine Park in Malaysia publication-title: Herpetol. Conserv. Biol. – volume: 7 start-page: 39 year: 2009 end-page: 53 ident: bb0130 article-title: Estimating population size, structure, and residency time for whale sharks publication-title: Endanger. Species Res. – volume: 16 start-page: 338 year: 2000 end-page: 354 ident: bb0030 article-title: Temporal variability in features used to photo-identify humpback whales ( publication-title: Mar. Mamm. Sci. – volume: 27 start-page: 393 year: 2007 end-page: 398 ident: bb0100 article-title: Individual identification of decapod crustaceans I: color patterns in rock shrimp ( publication-title: J. Crustac. Biol. – volume: 360 start-page: 103 year: 2008 end-page: 108 ident: bb0250 article-title: Investigating the viability of photo-identification as an objective tool to study endangered sea turtle populations publication-title: J. Exp. Mar. Biol. Ecol. – volume: 78 start-page: 1757 year: 2011 end-page: 1768 ident: bb0185 article-title: Photo-identification of individual weedy seadragons publication-title: J. Fish Biol. – volume: 476 start-page: 15 year: 2016 end-page: 21 ident: bb0040 article-title: Stability of facial scale patterns on green sea turtles Chelonia mydas over time: a validation for the use of a photo-identification method publication-title: J. Exp. Mar. Biol. Ecol. – volume: 20 start-page: 291 year: 2014 end-page: 300 ident: bb0295 article-title: Human visual identification of individual Andean bears publication-title: Wildl. Biol. – volume: 90 start-page: 1246 year: 2009 end-page: 1255 ident: bb0095 article-title: Sources and rates of errors in methods of individual identification for North Atlantic Right Whales publication-title: J. Mammal. – volume: 467 start-page: 115 year: 2015 end-page: 120 ident: bb0275 article-title: Applying a fast, effective and reliable photographic identification system for green turtles in the waters near Luichiu Island, Taiwan publication-title: J. Exp. Mar. Biol. Ecol. – volume: 18 start-page: 133 year: 2019 end-page: 144 ident: bb0020 article-title: Identifying Sea turtle home ranges utilizing citizen-science data from novel web-based and smartphone GIS applications publication-title: Chelonian Conserv. Biol. – start-page: 77 year: 2017 ident: bb0090 article-title: HotSpotter: less manipulating, more learning, and better vision for turtle photo identification publication-title: 37th Annual Symposium on Sea Turtle Biology and Conservation, Nevada – start-page: 7 year: 2018 ident: bb0240 article-title: The State of Kenya’s Grevy’s Zebras and Reticulated Giraffes: Results of the Great Grevy’s Rally 2018 (Technical Report) – volume: 121 start-page: 5 year: 2008 end-page: 9 ident: bb0080 article-title: In-water observations of recently-released juvenile hawksbills ( publication-title: Mar. Turt. Newsl. – volume: 26 start-page: 137 year: 2014 end-page: 146 ident: bb0085 article-title: Recognition of juvenile hawksbills publication-title: Endanger. Species Res. – volume: 84 start-page: 71 year: 2007 end-page: 80 ident: bb0115 article-title: Assessing the size, growth rate and structure of a seasonal population of whale sharks ( publication-title: Fish. Res. – start-page: 1 year: 2017 end-page: 8 ident: bb0025 article-title: Wildbook: Crowdsourcing, Computer Vision, and Data Science for Conservation – year: 2018 ident: bb0215 article-title: R: A Language and Environment for Statistical Computing – start-page: 316 year: 2000 ident: bb0230 article-title: Photo-identification of Hawaiian green sea turtles publication-title: Eighteenth International Sea Turtle Symposium – volume: 11 start-page: 12 year: 2015 end-page: 13 ident: bb0160 article-title: The Internet of Turtles. The State of the World's Sea Turtles (SWOT) – volume: 2 start-page: 148 year: 1996 end-page: 152 ident: bb0200 article-title: Use of PIT tags and photoidentification to revise remigration estimates of leatherback turtles ( publication-title: Chelonian Conserv. Biol. – volume: 8 start-page: e66035 year: 2013 ident: bb0280 article-title: Gauging the threat: the first population estimate for white sharks in South Africa using photo identification and automated software publication-title: PLoS One – volume: 8 start-page: e55935 year: 2013 ident: bb0260 article-title: Photographic capture-recapture sampling for assessing populations of the Indian gliding lizard publication-title: PLoS One – volume: 155 start-page: 15 year: 2018 end-page: 19 ident: bb0265 article-title: Evaluating the software I3S pattern for photo-identification of nesting hawksbill turtles ( publication-title: Mar. Turt. Newsl. – volume: 8 start-page: 145 year: 2010 end-page: 150 ident: bb0235 article-title: Analysis of whale shark publication-title: Aquat. Biol. – volume: 10 start-page: 10 year: 2015 end-page: 11 ident: bb0075 article-title: Picture perfect: Photography for hands-off turtle monitoring publication-title: The State of the World's Sea Turtles (SWOT) – volume: 27 start-page: 399 year: 2007 end-page: 403 ident: bb0110 article-title: Individual identification of decapod crustaceans II: natural and genetic markers in snow crab ( publication-title: J. Crustac. Biol. – volume: 101 start-page: e03027 year: 2020 ident: bb0255 article-title: Long-term photo-id and satellite tracking reveal sex-biased survival linked to movements in an endangered species publication-title: Ecology – volume: 589 start-page: 263 year: 2018 end-page: 268 ident: bb0035 article-title: I publication-title: Mar. Ecol. Prog. Ser. – volume: 82 start-page: 440 year: 2001 end-page: 449 ident: bb0150 article-title: Computer-aided photograph matching in studies using individual identification: an example from Serengeti cheetahs publication-title: J. Mammal. – volume: 452 start-page: 105 year: 2014 end-page: 110 ident: bb0045 article-title: Automated marine turtle photograph identification using artificial neural networks, with application to green turtles publication-title: J. Exp. Mar. Biol. Ecol. – volume: 91 start-page: 1350 year: 2010 end-page: 1359 ident: bb0010 article-title: Computer-aided photo-identification system with an application to polar bears based on whisker spot patterns publication-title: J. Mammal. – volume: 60 start-page: 91 year: 2004 end-page: 110 ident: bb0180 article-title: Distinctive image features from scale-invariant keypoints publication-title: Int. J. Comput. Vis. – start-page: 3650 year: 2012 end-page: 3656 ident: bb0190 article-title: Local Naive Bayes Nearest Neighbor for image classification publication-title: 2012 IEEE Conference on Computer Vision and Pattern Recognition, Rhode Island – volume: 5 start-page: 4117 year: 2014 ident: bb0270 article-title: Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures publication-title: Nat. Commun. – start-page: 417 year: 2008 end-page: 425 ident: bb0210 article-title: Leatherbacks matching by automated image recognition publication-title: Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects – year: 2014 ident: bb0070 article-title: I – volume: 94 start-page: 1464 year: 2013 end-page: 1471 ident: bb0195 article-title: Integrated modeling of bilateral photo-identification data in mark–recapture analyses publication-title: Ecology – volume: 37 start-page: 60 year: 2013 end-page: 66 ident: bb0155 article-title: Accurate identification of individual geckos ( publication-title: N. Z. J. Ecol. – volume: 152 start-page: 16 year: 2017 end-page: 19 ident: bb0015 article-title: Animal mapping using a citizen-science web-based GIS in the Bay Islands, Honduras publication-title: Mar. Turt. Newsl. – volume: 9 start-page: e96992 year: 2014 ident: bb0105 article-title: A face in the crowd: a non-invasive and cost effective photo-identification methodology to understand the fine scale movement of eastern water dragons publication-title: PLoS One – volume: 5 start-page: 73 year: 2008 end-page: 82 ident: bb0225 article-title: Photographic identification of sea turtles: method description and validation, with an estimation of tag loss publication-title: Endanger. Species Res. – volume: 12 start-page: 350 year: 2017 ident: 10.1016/j.jembe.2020.151490_bb0175 article-title: Using photographic identification to monitor sea turtle populations at Perhentian Islands Marine Park in Malaysia publication-title: Herpetol. Conserv. Biol. – volume: 146 start-page: 1 year: 2015 ident: 10.1016/j.jembe.2020.151490_bb0060 article-title: Photographic identification of green turtles (Chelonia mydas) at Redang Island, Malaysia publication-title: Mar. Turt. Newsl. – ident: 10.1016/j.jembe.2020.151490_bb0070 – start-page: 417 year: 2008 ident: 10.1016/j.jembe.2020.151490_bb0210 article-title: Leatherbacks matching by automated image recognition – volume: 121 start-page: 5 year: 2008 ident: 10.1016/j.jembe.2020.151490_bb0080 article-title: In-water observations of recently-released juvenile hawksbills (Eretmochelys imbricata) publication-title: Mar. Turt. Newsl. – volume: 360 start-page: 103 year: 2008 ident: 10.1016/j.jembe.2020.151490_bb0250 article-title: Investigating the viability of photo-identification as an objective tool to study endangered sea turtle populations publication-title: J. Exp. Mar. Biol. Ecol. doi: 10.1016/j.jembe.2008.04.005 – start-page: 77 year: 2017 ident: 10.1016/j.jembe.2020.151490_bb0090 article-title: HotSpotter: less manipulating, more learning, and better vision for turtle photo identification – volume: 273 start-page: 333 year: 2007 ident: 10.1016/j.jembe.2020.151490_bb0005 article-title: Can whisker spot patterns be used to identify individual polar bears? publication-title: J. Zool. doi: 10.1111/j.1469-7998.2007.00340.x – volume: 88 start-page: 800 year: 2016 ident: 10.1016/j.jembe.2020.151490_bb0055 article-title: Photo-identification as a simple tool for studying invasive lionfish Pterois volitans populations publication-title: J. Fish Biol. doi: 10.1111/jfb.12857 – volume: 10 start-page: 10 year: 2015 ident: 10.1016/j.jembe.2020.151490_bb0075 article-title: Picture perfect: Photography for hands-off turtle monitoring – volume: 32 start-page: 43 year: 2014 ident: 10.1016/j.jembe.2020.151490_bb0290 article-title: First assay of photo-identification in marine turtles' nesting population publication-title: Rev. Investig. Mar. – start-page: 1 year: 2017 ident: 10.1016/j.jembe.2020.151490_bb0025 – volume: 452 start-page: 105 year: 2014 ident: 10.1016/j.jembe.2020.151490_bb0045 article-title: Automated marine turtle photograph identification using artificial neural networks, with application to green turtles publication-title: J. Exp. Mar. Biol. Ecol. doi: 10.1016/j.jembe.2013.12.010 – volume: 18 start-page: 133 issue: 2 year: 2019 ident: 10.1016/j.jembe.2020.151490_bb0020 article-title: Identifying Sea turtle home ranges utilizing citizen-science data from novel web-based and smartphone GIS applications publication-title: Chelonian Conserv. Biol. doi: 10.2744/CCB-1355.1 – start-page: 1 year: 2018 ident: 10.1016/j.jembe.2020.151490_bb0205 article-title: An animal detection pipeline for identification – year: 2018 ident: 10.1016/j.jembe.2020.151490_bb0215 – volume: 476 start-page: 15 year: 2016 ident: 10.1016/j.jembe.2020.151490_bb0040 article-title: Stability of facial scale patterns on green sea turtles Chelonia mydas over time: a validation for the use of a photo-identification method publication-title: J. Exp. Mar. Biol. Ecol. doi: 10.1016/j.jembe.2015.12.003 – volume: 18 start-page: 222 year: 2008 ident: 10.1016/j.jembe.2020.151490_bb0125 article-title: Robust, comparable population metrics through collaborative photo-monitoring of whale sharks Rhincodon typus publication-title: Ecol. Appl. doi: 10.1890/07-0315.1 – volume: 589 start-page: 263 year: 2018 ident: 10.1016/j.jembe.2020.151490_bb0035 article-title: I3S pattern as a mark-recapture tool to identify captured and free-swimming sea turtles: an assessment publication-title: Mar. Ecol. Prog. Ser. doi: 10.3354/meps12483 – volume: 137 start-page: 1 year: 2013 ident: 10.1016/j.jembe.2020.151490_bb0050 article-title: Unraveling behavioral patterns of foraging hawksbill and green turtles using photo-identification publication-title: Mar. Turt. Newsl. – volume: 8 start-page: e55935 issue: 2 year: 2013 ident: 10.1016/j.jembe.2020.151490_bb0260 article-title: Photographic capture-recapture sampling for assessing populations of the Indian gliding lizard Draco dussumieri publication-title: PLoS One doi: 10.1371/journal.pone.0055935 – volume: 8 start-page: e66035 year: 2013 ident: 10.1016/j.jembe.2020.151490_bb0280 article-title: Gauging the threat: the first population estimate for white sharks in South Africa using photo identification and automated software publication-title: PLoS One doi: 10.1371/journal.pone.0066035 – start-page: 316 year: 2000 ident: 10.1016/j.jembe.2020.151490_bb0230 article-title: Photo-identification of Hawaiian green sea turtles – volume: 27 start-page: 393 year: 2007 ident: 10.1016/j.jembe.2020.151490_bb0100 article-title: Individual identification of decapod crustaceans I: color patterns in rock shrimp (Rhynchocinetes typus) publication-title: J. Crustac. Biol. doi: 10.1651/S-2773.1 – volume: 2012 start-page: 1 year: 2012 ident: 10.1016/j.jembe.2020.151490_bb0165 article-title: Methods of developing user-friendly keys to identify Green Sea turtles (Chelonia mydas L.) from photographs publication-title: Int. J. Zool. doi: 10.1155/2012/317568 – volume: 90 start-page: 1246 year: 2009 ident: 10.1016/j.jembe.2020.151490_bb0095 article-title: Sources and rates of errors in methods of individual identification for North Atlantic Right Whales publication-title: J. Mammal. doi: 10.1644/08-MAMM-A-328.1 – volume: 5 start-page: 73 year: 2008 ident: 10.1016/j.jembe.2020.151490_bb0225 article-title: Photographic identification of sea turtles: method description and validation, with an estimation of tag loss publication-title: Endanger. Species Res. doi: 10.3354/esr00113 – start-page: 7 year: 2018 ident: 10.1016/j.jembe.2020.151490_bb0240 – volume: 26 start-page: 137 year: 2014 ident: 10.1016/j.jembe.2020.151490_bb0085 article-title: Recognition of juvenile hawksbills Eretmochelys imbricata through face scale digitization and automated searching publication-title: Endanger. Species Res. doi: 10.3354/esr00637 – volume: 78 start-page: 1757 year: 2011 ident: 10.1016/j.jembe.2020.151490_bb0185 article-title: Photo-identification of individual weedy seadragons Phyllopteryx taeniolatus and its application in estimating population dynamics publication-title: J. Fish Biol. doi: 10.1111/j.1095-8649.2011.02966.x – volume: 152 start-page: 16 year: 2017 ident: 10.1016/j.jembe.2020.151490_bb0015 article-title: Animal mapping using a citizen-science web-based GIS in the Bay Islands, Honduras publication-title: Mar. Turt. Newsl. – volume: 155 start-page: 15 year: 2018 ident: 10.1016/j.jembe.2020.151490_bb0265 article-title: Evaluating the software I3S pattern for photo-identification of nesting hawksbill turtles (Eretmochelys imbricata) publication-title: Mar. Turt. Newsl. – volume: 467 start-page: 115 year: 2015 ident: 10.1016/j.jembe.2020.151490_bb0275 article-title: Applying a fast, effective and reliable photographic identification system for green turtles in the waters near Luichiu Island, Taiwan publication-title: J. Exp. Mar. Biol. Ecol. doi: 10.1016/j.jembe.2015.03.003 – volume: 16 start-page: 338 year: 2000 ident: 10.1016/j.jembe.2020.151490_bb0030 article-title: Temporal variability in features used to photo-identify humpback whales (Megaptera novaeangliae) publication-title: Mar. Mamm. Sci. doi: 10.1111/j.1748-7692.2000.tb00929.x – volume: 9 start-page: e96992 year: 2014 ident: 10.1016/j.jembe.2020.151490_bb0105 article-title: A face in the crowd: a non-invasive and cost effective photo-identification methodology to understand the fine scale movement of eastern water dragons publication-title: PLoS One doi: 10.1371/journal.pone.0096992 – volume: 60 start-page: 91 issue: 2 year: 2004 ident: 10.1016/j.jembe.2020.151490_bb0180 article-title: Distinctive image features from scale-invariant keypoints publication-title: Int. J. Comput. Vis. doi: 10.1023/B:VISI.0000029664.99615.94 – volume: 101 start-page: e03027 year: 2020 ident: 10.1016/j.jembe.2020.151490_bb0255 article-title: Long-term photo-id and satellite tracking reveal sex-biased survival linked to movements in an endangered species publication-title: Ecology doi: 10.1002/ecy.3027 – volume: 7 start-page: 39 year: 2009 ident: 10.1016/j.jembe.2020.151490_bb0130 article-title: Estimating population size, structure, and residency time for whale sharks Rhincodon typus through collaborative photo-identification publication-title: Endanger. Species Res. doi: 10.3354/esr00186 – volume: 11 start-page: 8 year: 2010 ident: 10.1016/j.jembe.2020.151490_bb0135 article-title: Photo-identification method for green and hawksbill turtles - first results from Reunion publication-title: Indian Ocean Turtle Newsl. – volume: 37 start-page: 60 year: 2013 ident: 10.1016/j.jembe.2020.151490_bb0155 article-title: Accurate identification of individual geckos (Naultinus gemmeus) through dorsal pattern differentiation publication-title: N. Z. J. Ecol. – volume: 27 start-page: 399 year: 2007 ident: 10.1016/j.jembe.2020.151490_bb0110 article-title: Individual identification of decapod crustaceans II: natural and genetic markers in snow crab (Chionoecetes opilio) publication-title: J. Crustac. Biol. doi: 10.1651/S-2771.1 – volume: 84 start-page: 71 issue: 1 year: 2007 ident: 10.1016/j.jembe.2020.151490_bb0115 article-title: Assessing the size, growth rate and structure of a seasonal population of whale sharks (Rhincodon typus Smith 1828) using conventional tagging and photo identification publication-title: Fish. Res. doi: 10.1016/j.fishres.2006.11.026 – start-page: 3650 year: 2012 ident: 10.1016/j.jembe.2020.151490_bb0190 article-title: Local Naive Bayes Nearest Neighbor for image classification – start-page: 230 year: 2013 ident: 10.1016/j.jembe.2020.151490_bb0065 article-title: HotSpotter – Patterned species instance recognition – volume: 25 start-page: 311 year: 2018 ident: 10.1016/j.jembe.2020.151490_bb0285 article-title: Consistency of coloriation pattern and applicability of photo identification method as a tool to identify Kaiser's mountain newt, Neurergus kaiseri publication-title: Russ. J. Herpetol. doi: 10.30906/1026-2296-2018-25-4-311-321 – volume: 11 start-page: 12 year: 2015 ident: 10.1016/j.jembe.2020.151490_bb0160 – volume: 8 start-page: 145 year: 2010 ident: 10.1016/j.jembe.2020.151490_bb0235 article-title: Analysis of whale shark Rhincodon typus aggregations near South Ari Atoll, Maldives Archipelago publication-title: Aquat. Biol. doi: 10.3354/ab00215 – volume: 31 start-page: 489 year: 2010 ident: 10.1016/j.jembe.2020.151490_bb0245 article-title: Photographic identification in reptiles: a matter of scales publication-title: Amphib.-Reptil. doi: 10.1163/017353710X521546 – volume: 25 start-page: 1 year: 2017 ident: 10.1016/j.jembe.2020.151490_bb0120 article-title: Impacts of recreational diving on hawksbill sea turtle (Eretmochelys imbricata) behaviour in a marine protected area publication-title: J. Sustain. Tour. doi: 10.1080/09669582.2016.1174246 – volume: 34 start-page: 628 year: 2005 ident: 10.1016/j.jembe.2020.151490_bb0145 article-title: Photo-identification, site fidelity, and movement of female gray seals (Halichoerus grypus) between haul-outs in the Baltic Sea publication-title: AMBIO doi: 10.1579/0044-7447-34.8.628 – volume: 82 start-page: 440 issue: 2 year: 2001 ident: 10.1016/j.jembe.2020.151490_bb0150 article-title: Computer-aided photograph matching in studies using individual identification: an example from Serengeti cheetahs publication-title: J. Mammal. doi: 10.1644/1545-1542(2001)082<0440:CAPMIS>2.0.CO;2 – volume: 150 start-page: 4 year: 2016 ident: 10.1016/j.jembe.2020.151490_bb0170 article-title: Identification of a dead green turtle (Chelonia mydas) using photographic identification publication-title: Mar. Turt. Newsl. – volume: 254 start-page: 1 issue: 1 year: 2001 ident: 10.1016/j.jembe.2020.151490_bb0140 article-title: Censusing and monitoring black rhino (Diceros bicornis) using an objective spoor (footprint) identification technique publication-title: J. Zool. doi: 10.1017/S0952836901000516 – volume: 2 start-page: 148 year: 1996 ident: 10.1016/j.jembe.2020.151490_bb0200 article-title: Use of PIT tags and photoidentification to revise remigration estimates of leatherback turtles (Dermochelys coriacea) nesting in St. Croix, U.S. Virgin Islands, 1979-1995 publication-title: Chelonian Conserv. Biol. – volume: 94 start-page: 1464 year: 2013 ident: 10.1016/j.jembe.2020.151490_bb0195 article-title: Integrated modeling of bilateral photo-identification data in mark–recapture analyses publication-title: Ecology doi: 10.1890/12-1613.1 – volume: 20 start-page: 291 issue: 5 year: 2014 ident: 10.1016/j.jembe.2020.151490_bb0295 article-title: Human visual identification of individual Andean bears Tremarctos ornatus publication-title: Wildl. Biol. doi: 10.2981/wlb.00023 – volume: 5 start-page: 4117 year: 2014 ident: 10.1016/j.jembe.2020.151490_bb0270 article-title: Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures publication-title: Nat. Commun. doi: 10.1038/ncomms5117 – volume: 91 start-page: 1350 year: 2010 ident: 10.1016/j.jembe.2020.151490_bb0010 article-title: Computer-aided photo-identification system with an application to polar bears based on whisker spot patterns publication-title: J. Mammal. doi: 10.1644/09-MAMM-A-425.1 – volume: 10 start-page: 29 year: 1998 ident: 10.1016/j.jembe.2020.151490_bb0220 article-title: Photo-identification of Stichopus mollis publication-title: SPC Beche-de mer Inf. Bull. |
| SSID | ssj0001526 |
| Score | 2.4773538 |
| Snippet | Photo identification (PID) in animal studies has been a widely used method for identifying individuals of many species based on unique natural markings and... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 151490 |
| SubjectTerms | Computer-automated algorithms Eretmochelys imbricata face Internet Marine turtles Photo identification Sea turtle database management sea turtles wildlife |
| Title | HotSpotter: Using a computer-driven photo-id application to identify sea turtles |
| URI | https://dx.doi.org/10.1016/j.jembe.2020.151490 https://www.proquest.com/docview/2551918570 |
| Volume | 535 |
| WOSCitedRecordID | wos000602892800004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: ScienceDirect Freedom Collection - Elsevier customDbUrl: eissn: 1879-1697 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001526 issn: 0022-0981 databaseCode: AIEXJ dateStart: 19950116 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1ba9swFBZZusEYjF1ZuwsejL1kKpbl2NbewkjptpIGlkLehCVLLKG13cTt2n-_I1lK0m4t3cNejDDyBZ0P6dPROedD6EMcU5kQHeIoIzGOSSGwSAqCdZJGhUqpJkVhxSbS0SibTtm40_nlc2HOj9OyzC4uWP1fTQ33wNgmdfYfzL16KdyANhgdrmB2uN7J8PtV86OuTJKO2e23IQG5DR036g24WJj5rVf_rJoKz4rexgm24aEzm7irL3smhRKWI3jj8gYCe0Uc4CQ3aYS9zZpOSl5x2QNVFm00t4ssW8t6DYxr0c7KVkJ67bkd5wufx50bqcTVsdR3mxNmvbxGdWjTdxERH-6sN3MJQtaKtvj5uE_7vXoXmEjMQvzXWb51OMx35-pEmFKnUei6rxc1f5A_OuR7RwcHfDKcTj7Wp9jIjZljeae9cg9tRWmfZV20Nfg6nH5bLeJAaxJfaN78oC9YZUMD__juTaTm2vJuOcvkCXrsbBUMWpA8RR1VPkMPWvnRS2gNpWs9OpQqL1318udovMbQ58AiKMiDawgKPIKCDQQFTRV4BAWAoMAh6AU62htOvuxjJ72BJaVJg4UoMkW1AHabp0VOYRuaJVnGJIFVSfb7CnieIlRHMtWF1lSkaUi0YMqo11Mp6UvULatSvUIBFSELC9hl6DiOM5oJxnJqtgFJShSNw20U-bHj0tWlN_Iox9wHIM65HXBuBpy3A76NPq0eqtuyLLd3T7xRuGOWLWPkAKnbH3zvTchh3jWHaXmpqrMlh604YaaQWrhzhz6v0cM1_t-gbrM4U2_RfXnezJaLdw58vwGutqTV |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=HotSpotter%3A+Using+a+computer-driven+photo-id+application+to+identify+sea+turtles&rft.jtitle=Journal+of+experimental+marine+biology+and+ecology&rft.au=Dunbar%2C+Stephen+G&rft.au=Anger%2C+Edward+C&rft.au=Parham%2C+Jason+R&rft.au=Kingen%2C+Colin&rft.date=2021-02-01&rft.issn=0022-0981&rft.volume=535+p.151490-&rft_id=info:doi/10.1016%2Fj.jembe.2020.151490&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0022-0981&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0022-0981&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0022-0981&client=summon |