Teat detection algorithm: YOLO vs. Haar-cascade

In this study we have developed and experimented with two methods of teat detection based on machine learning approach in image recognition and object detection. Automatic milking systems rely strongly on the vision system for successful milking operation initiation which is the attachment of the te...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of mechanical science and technology Jg. 33; H. 4; S. 1869 - 1874
Hauptverfasser: Rastogi, Akanksha, Ryuh, Beom Sahng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Seoul Korean Society of Mechanical Engineers 01.04.2019
Springer Nature B.V
대한기계학회
Schlagworte:
Algorithms
Control
Dynamical Systems
Edge detection
Engineering
Image processing
Indoor environments
Industrial and Production Engineering
Machine learning
Machine vision
Mechanical Engineering
Neural networks
Object recognition
Vibration
Vision systems
기계공학
YOLO
Automatic milking systems
Haar-cascade
Teat detection
ISSN:1738-494X, 1976-3824
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract In this study we have developed and experimented with two methods of teat detection based on machine learning approach in image recognition and object detection. Automatic milking systems rely strongly on the vision system for successful milking operation initiation which is the attachment of the teat cups correctly. Teat detection method currently employed in the industry is based on laser assisted edge detection mechanism, making the current systems less advanced than the existing methods in the field of image processing and robotic vision. By experimenting on a basic object detection method based on Haar-like features, viz. Haar cascade classification method and a latest state-of-the-art method based on convolutional neural nets, viz. YOLO-object detection method, we have compared the results of detection on a fake teat model casted from silicon, especially for indoor environments. This study is in extension to the successful real time detection in a cow farm using Haar-cascade based algorithm.
AbstractList In this study we have developed and experimented with two methods of teat detection based on machine learning approach in image recognition and object detection. Automatic milking systems rely strongly on the vision system for successful milking operation initiation which is the attachment of the teat cups correctly. Teat detection method currently employed in the industry is based on laser assisted edge detection mechanism, making the current systems less advanced than the existing methods in the field of image processing and robotic vision. By experimenting on a basic object detection method based on Haar-like features, viz. Haar cascade classification method and a latest state-of-the-art method based on convolutional neural nets, viz. YOLO-object detection method, we have compared the results of detection on a fake teat model casted from silicon, especially for indoor environments. This study is in extension to the successful real time detection in a cow farm using Haar-cascade based algorithm.
In this study we have developed and experimented with two methods of teat detection based on machine learning approach in image recognition and object detection. Automatic milking systems rely strongly on the vision system for successful milking operation initiation which is the attachment of the teat cups correctly. Teat detection method currently employed in the industry is based on laser assisted edge detection mechanism, making the current systems less advanced than the existing methods in the field of image processing and robotic vision. By experimenting on a basic object detection method based on Haar-like features, viz. Haar cascade classification method and a latest state-of-the-art method based on convolutional neural nets, viz. YOLO-object detection method, we have compared the results of detection on a fake teat model casted from silicon, especially for indoor environments. This study is in extension to the successful real time detection in a cow farm using Haar-cascade based algorithm. KCI Citation Count: 1
Author Ryuh, Beom Sahng
Rastogi, Akanksha
Author_xml – sequence: 1
  givenname: Akanksha
  surname: Rastogi
  fullname: Rastogi, Akanksha
  email: akankshar@jbnu.ac.kr
  organization: School of Mechanical Systems Engineering, Chonbuk National University
– sequence: 2
  givenname: Beom Sahng
  surname: Ryuh
  fullname: Ryuh, Beom Sahng
  organization: School of Mechanical Systems Engineering, Chonbuk National University
BackLink https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002456065$$DAccess content in National Research Foundation of Korea (NRF)
BookMark eNp9kE1LAzEURYNUsK3-AHcDrlykzddMJu5KUVsoFKQLXYVMJqnTj0lNUsF_b-oIgqCr-xb3vPc4A9BrXWsAuMZohBHi44AJQQVEWEBEqYD5GehjwQtIS8J6aea0hEyw5wswCGGDUEEYxn0wXhkVs9pEo2Pj2kzt1s438XV_l70sF8vsPYyymVIeahW0qs0lOLdqF8zVdw7B6uF-NZ3BxfJxPp0soKY5ipAoXmjEiKoML3CpmC2xqUxBudGCImtLxKnIayMqkYvaWk7rKheksGVe1TUdgttubeut3OpGOtV85drJrZeTp9VcMk4wJzR1b7ruwbu3owlRbtzRt-k7SViZ7DCBRGrhrqW9C8EbKw--2Sv_ITGSJ4WyUyiTQnlSKPPE8F-MbqI6eYpeNbt_SdKRIV1p18b__PQ39Aku4YSg
CitedBy_id crossref_primary_10_1007_s11042_022_13644_y
crossref_primary_10_1016_j_biosystemseng_2025_104142
crossref_primary_10_1016_j_compag_2022_107224
crossref_primary_10_3390_electronics9121993
crossref_primary_10_1016_j_matpr_2020_11_562
crossref_primary_10_1016_j_compag_2020_105216
crossref_primary_10_1016_j_compag_2021_106391
crossref_primary_10_1016_j_jclepro_2023_137558
Cites_doi 10.1109/ICCSCE.2017.8284383
10.1006/jcss.1997.1504
ContentType Journal Article
Copyright KSME & Springer 2019
KSME & Springer 2019.
Copyright_xml – notice: KSME & Springer 2019
– notice: KSME & Springer 2019.
DBID AAYXX
CITATION
7TB
8FD
8FE
8FG
ABJCF
AFKRA
ARAPS
BENPR
BGLVJ
CCPQU
DWQXO
FR3
HCIFZ
L6V
M7S
P5Z
P62
PHGZM
PHGZT
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PTHSS
S0W
ACYCR
DOI 10.1007/s12206-019-0339-5
DatabaseName CrossRef
Mechanical & Transportation Engineering Abstracts
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
Materials Science & Engineering Collection
ProQuest Central UK/Ireland
Advanced Technologies & Computer Science Collection
ProQuest Central
ProQuest Technology Collection
ProQuest One
ProQuest Central Korea
Engineering Research Database
SciTech Premium Collection
ProQuest Engineering Collection
Engineering Database
Advanced Technologies & Aerospace Database
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Premium
ProQuest One Academic (New)
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
Engineering Collection
DELNET Engineering & Technology Collection
Korean Citation Index
DatabaseTitle CrossRef
Technology Collection
Technology Research Database
ProQuest One Academic Middle East (New)
Mechanical & Transportation Engineering Abstracts
ProQuest Advanced Technologies & Aerospace Collection
SciTech Premium Collection
ProQuest One Community College
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest Engineering Collection
ProQuest Central Korea
ProQuest Central (New)
Engineering Collection
Advanced Technologies & Aerospace Collection
Engineering Database
ProQuest One Academic Eastern Edition
ProQuest Technology Collection
ProQuest SciTech Collection
Advanced Technologies & Aerospace Database
ProQuest One Academic UKI Edition
ProQuest DELNET Engineering and Technology Collection
Materials Science & Engineering Collection
Engineering Research Database
ProQuest One Academic
ProQuest One Academic (New)
DatabaseTitleList Technology Collection
Database_xml – sequence: 1
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1976-3824
EndPage 1874
ExternalDocumentID oai_kci_go_kr_ARTI_4721723
10_1007_s12206_019_0339_5
GroupedDBID -5B
-5G
-BR
-EM
-Y2
-~C
.86
.UV
.VR
06D
0R~
0VY
1N0
2.D
203
29L
29~
2J2
2JN
2JY
2KG
2KM
2LR
2VQ
2~H
30V
4.4
406
408
40D
40E
5GY
5VS
6NX
8FE
8FG
8UJ
95-
95.
95~
96X
9ZL
AAAVM
AABHQ
AACDK
AAHNG
AAIAL
AAJBT
AAJKR
AANZL
AARHV
AARTL
AASML
AATNV
AATVU
AAUYE
AAWCG
AAYIU
AAYQN
AAYTO
AAYZH
ABAKF
ABDZT
ABECU
ABFTD
ABFTV
ABHQN
ABJCF
ABJNI
ABJOX
ABKCH
ABMNI
ABMQK
ABNWP
ABQBU
ABQSL
ABSXP
ABTEG
ABTHY
ABTKH
ABTMW
ABWNU
ABXPI
ACAOD
ACBXY
ACDTI
ACGFS
ACHSB
ACHXU
ACIWK
ACKNC
ACMDZ
ACMLO
ACOKC
ACOMO
ACPIV
ACSNA
ACZOJ
ADHIR
ADINQ
ADKNI
ADKPE
ADMLS
ADRFC
ADTPH
ADURQ
ADYFF
ADZKW
AEBTG
AEFQL
AEGAL
AEGNC
AEJHL
AEJRE
AEKMD
AEMSY
AENEX
AEOHA
AEPYU
AESKC
AETLH
AEVLU
AEXYK
AFBBN
AFGCZ
AFKRA
AFLOW
AFQWF
AFWTZ
AFZKB
AGAYW
AGDGC
AGJBK
AGMZJ
AGQEE
AGQMX
AGRTI
AGWIL
AGWZB
AGYKE
AHAVH
AHBYD
AHKAY
AHSBF
AHYZX
AIAKS
AIGIU
AIIXL
AILAN
AITGF
AJBLW
AJRNO
ALMA_UNASSIGNED_HOLDINGS
ALWAN
AMKLP
AMXSW
AMYLF
AOCGG
ARCEE
ARMRJ
ASPBG
AVWKF
AXYYD
AYJHY
AZFZN
B-.
BA0
BDATZ
BENPR
BGLVJ
CAG
CCPQU
COF
CS3
CSCUP
DBRKI
DDRTE
DNIVK
DPUIP
EBLON
EBS
EIOEI
EJD
ESBYG
FEDTE
FERAY
FFXSO
FIGPU
FINBP
FNLPD
FRRFC
FSGXE
FWDCC
GGCAI
GGRSB
GJIRD
GNWQR
GQ6
GQ7
GW5
H13
HCIFZ
HF~
HG6
HMJXF
HRMNR
HVGLF
HZ~
I-F
IJ-
IKXTQ
IWAJR
IXC
IXD
I~X
I~Z
J-C
J0Z
JBSCW
JZLTJ
KOV
KVFHK
L6V
LLZTM
M7S
MA-
MK~
ML~
MZR
NDZJH
NF0
NPVJJ
NQJWS
O9-
P9P
PF0
PT4
PTHSS
Q2X
QOS
R89
R9I
RHV
ROL
RPX
RSV
S0W
S16
S1Z
S26
S27
S28
S3B
SAP
SCLPG
SDH
SEG
SHX
SISQX
SJYHP
SNE
SNPRN
SNX
SOHCF
SOJ
SPISZ
SRMVM
SSLCW
STPWE
SZN
T13
T16
TDB
TSG
TSV
TUC
TUS
U2A
UG4
UOJIU
UTJUX
UZXMN
VC2
VFIZW
W48
WK8
YLTOR
Z45
Z5O
Z7R
Z7S
Z7V
Z7W
Z7X
Z7Y
Z7Z
Z81
Z83
Z85
Z86
Z88
Z8M
Z8R
Z8T
Z8W
ZMTXR
ZZE
~A9
AAPKM
AAYXX
ABDBE
ABFSG
ABRTQ
ACSTC
ADHKG
AEZWR
AFDZB
AFFHD
AFHIU
AFOHR
AGQPQ
AHPBZ
AHWEU
AIXLP
ARAPS
ATHPR
CITATION
PHGZM
PHGZT
PQGLB
7TB
8FD
DWQXO
FR3
P62
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
AABYN
AAFGU
AAYFA
ABFGW
ABKAS
ACBMV
ACBRV
ACBYP
ACIGE
ACIPQ
ACTTH
ACVWB
ACWMK
ACYCR
ADMDM
ADMVV
ADOXG
AEEQQ
AEFTE
AEKVL
AESTI
AEVTX
AFNRJ
AGGBP
AIMYW
AJDOV
AKQUC
SCV
UNUBA
ID FETCH-LOGICAL-c350t-2a76c042abe7618a4f81ebe637ec930ff807395de9b959dff73db5926f85bdd3
IEDL.DBID RSV
ISICitedReferencesCount 10
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000464749300039&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1738-494X
IngestDate Tue Nov 21 21:47:01 EST 2023
Wed Sep 17 23:58:37 EDT 2025
Tue Nov 18 22:29:51 EST 2025
Sat Nov 29 06:31:34 EST 2025
Fri Feb 21 02:31:16 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 4
Keywords YOLO
Automatic milking systems
Haar-cascade
Teat detection
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c350t-2a76c042abe7618a4f81ebe637ec930ff807395de9b959dff73db5926f85bdd3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
PQID 2481004909
PQPubID 326249
PageCount 6
ParticipantIDs nrf_kci_oai_kci_go_kr_ARTI_4721723
proquest_journals_2481004909
crossref_primary_10_1007_s12206_019_0339_5
crossref_citationtrail_10_1007_s12206_019_0339_5
springer_journals_10_1007_s12206_019_0339_5
PublicationCentury 2000
PublicationDate 20190400
2019-4-00
20190401
2019-04
PublicationDateYYYYMMDD 2019-04-01
PublicationDate_xml – month: 4
  year: 2019
  text: 20190400
PublicationDecade 2010
PublicationPlace Seoul
PublicationPlace_xml – name: Seoul
– name: Heidelberg
PublicationTitle Journal of mechanical science and technology
PublicationTitleAbbrev J Mech Sci Technol
PublicationYear 2019
Publisher Korean Society of Mechanical Engineers
Springer Nature B.V
대한기계학회
Publisher_xml – name: Korean Society of Mechanical Engineers
– name: Springer Nature B.V
– name: 대한기계학회
References Marinello, Pezzuolo, Gasparini, Arvidsson, Sartori (CR1) 2015; 5
Hofman, Rujiter, Koekoek, Williem ver der Sluis (CR3) 2012
Jay (CR17) 2016
CR4
De Koning, van der Vost, Meijering (CR2) 2002
CR7
Kortekaas (CR8) 2015
Akhloufi (CR5) 2013
Freund, Schapire (CR11) 1997; 55
Redmon, Farhadi (CR15) 2016
Wilson, Fernandez (CR9) 2006; 21
Trieu (CR16) 2016
Rezaei (CR12) 2014
Redmon, Divvala, Girshick, Farhadi (CR14) 2015
Rastogi, Pal, Ryuh (CR13) 2017
(CR6) 2016
Viola, Jones (CR10) 2001
M Jay (339_CR17) 2016
K De Koning (339_CR2) 2002
P Viola (339_CR10) 2001
M Rezaei (339_CR12) 2014
J Redmon (339_CR15) 2016
H Hofman (339_CR3) 2012
A Rastogi (339_CR13) 2017
M P Kortekaas (339_CR8) 2015
J Redmon (339_CR14) 2015
F Marinello (339_CR1) 2015; 5
339_CR4
Gartner’s Inc Gartner Hype Cycle for Emerging Technologies (339_CR6) 2016
T H Trieu (339_CR16) 2016
339_CR7
M A Akhloufi (339_CR5) 2013
Y Freund (339_CR11) 1997; 55
P I Wilson (339_CR9) 2006; 21
References_xml – volume: 21
  start-page: 127
  issue: 4
  year: 2006
  end-page: 133
  ident: CR9
  article-title: Facial feature detection using Haar classifiers
  publication-title: Journal of Computing Science in Colleges
– year: 2015
  ident: CR14
  publication-title: You Only Look Once: Unified, Real-time Object Detection
– year: 2016
  ident: CR15
  publication-title: Yolo9000: Better, Faster, Stronger
– year: 2016
  ident: CR16
  publication-title: Darkflow
– start-page: 1
  year: 2002
  end-page: 11
  ident: CR2
  publication-title: Automatic Milking Experience and Development in Europe
– ident: CR4
– start-page: 74
  year: 2017
  end-page: 79
  ident: CR13
  article-title: Real-time teat detection using haar cascade classifier in smart automatic milking system
  publication-title: 2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)
  doi: 10.1109/ICCSCE.2017.8284383
– year: 2012
  ident: CR3
  article-title: milking box with robotic attacher and vision system
  publication-title: US 2012/0272914 A1
– year: 2016
  ident: CR17
  publication-title: YOLO Series
– year: 2013
  ident: CR5
  article-title: 3D vision system for intelligent milking robot automation
  publication-title: SPIE, Proceedings of the International Society for Optical Engineering
– year: 2016
  ident: CR6
  publication-title: Gartner’s Inc Connecticut
– year: 2015
  ident: CR8
  publication-title: Milking Robot for Attaching a Teat Cup
– year: 2014
  ident: CR12
  publication-title: Creating a Cascade of Haar Like Classifiers Step by Step
– volume: 55
  start-page: 119
  issue: 1
  year: 1997
  end-page: 139
  ident: CR11
  article-title: A decision-theoretic generalization of on-line learning and an application to boosting
  publication-title: Journal of Computer and System Science
  doi: 10.1006/jcss.1997.1504
– ident: CR7
– volume: 5
  start-page: 1
  year: 2015
  end-page: 12
  ident: CR1
  article-title: Application of Kinect sensor for dynamic soil surface characterization
  publication-title: Precision Agriculture
– year: 2001
  ident: CR10
  article-title: Rapid object detection using boosted cascade of simple features
  publication-title: IEEE Conference on Computer Vision and Pattern Recognition
– volume-title: Creating a Cascade of Haar Like Classifiers Step by Step
  year: 2014
  ident: 339_CR12
– start-page: 74
  volume-title: 2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)
  year: 2017
  ident: 339_CR13
  doi: 10.1109/ICCSCE.2017.8284383
– volume-title: Gartner’s Inc Connecticut
  year: 2016
  ident: 339_CR6
– volume-title: Yolo9000: Better, Faster, Stronger
  year: 2016
  ident: 339_CR15
– volume: 5
  start-page: 1
  year: 2015
  ident: 339_CR1
  publication-title: Precision Agriculture
– start-page: 1
  volume-title: Automatic Milking Experience and Development in Europe
  year: 2002
  ident: 339_CR2
– volume-title: Darkflow
  year: 2016
  ident: 339_CR16
– volume-title: YOLO Series
  year: 2016
  ident: 339_CR17
– volume: 21
  start-page: 127
  issue: 4
  year: 2006
  ident: 339_CR9
  publication-title: Journal of Computing Science in Colleges
– volume-title: US 2012/0272914 A1
  year: 2012
  ident: 339_CR3
– volume-title: You Only Look Once: Unified, Real-time Object Detection
  year: 2015
  ident: 339_CR14
– volume-title: IEEE Conference on Computer Vision and Pattern Recognition
  year: 2001
  ident: 339_CR10
– volume-title: Milking Robot for Attaching a Teat Cup
  year: 2015
  ident: 339_CR8
– volume-title: SPIE, Proceedings of the International Society for Optical Engineering
  year: 2013
  ident: 339_CR5
– ident: 339_CR4
– volume: 55
  start-page: 119
  issue: 1
  year: 1997
  ident: 339_CR11
  publication-title: Journal of Computer and System Science
  doi: 10.1006/jcss.1997.1504
– ident: 339_CR7
SSID ssj0062411
Score 2.2093897
Snippet In this study we have developed and experimented with two methods of teat detection based on machine learning approach in image recognition and object...
SourceID nrf
proquest
crossref
springer
SourceType Open Website
Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 1869
SubjectTerms Algorithms
Control
Dynamical Systems
Edge detection
Engineering
Image processing
Indoor environments
Industrial and Production Engineering
Machine learning
Machine vision
Mechanical Engineering
Neural networks
Object recognition
Vibration
Vision systems
기계공학
SummonAdditionalLinks – databaseName: Engineering Database
  dbid: M7S
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3NS8MwFH-46UEPfovTKUU8KdG26UfiRUQcCqKCQ-YppGkyxdnNtu7vN8lap4JePPXQNi3vM8l7-f0A9hWnUayljww5IQqoIogIF6MoTGScJMJXlnnu4Tq-uSG9Hr2rNtyKqq2yjok2UKdDYfbIj_2AeLZMRU9Hb8iwRpnqakWh0YBZg5Lg2da9-zoSRzo72QVXrJ06oEGvrmrao3O-b9fSFLkYUxR-y0uNLFffppw_qqQ2-XSW_vvby7BYTTuds4mdrMCMzFZh4QsY4Rocd3VYdlJZ2uaszOGDvh6ofHo9cR5vr2-dcXHkXHKeI8EL01S_Dt3ORff8ElV0Ckjg0C2Rz-NIaB_lWguRR3igiKdVGOFYCopdpYit2qWSJjSkqVIxTpOQ-pEiYZKmeAOa2TCTm-AkelZHiUsSKgPDWG0QX4QrJOV-yDEJWuDWsmSigho3jBcDNgVJNuJnWvzMiJ-FLTj4fGU0wdn46-E9rSD2Ip6ZQcc21_6QveRMrwGuWBAb0i3cgnatEVb5ZcGm6mjBYa3T6e1fv7j192DbMO9bUzIdPW1olvm73IE5MS6fi3zXGuUHrOTiyg
  priority: 102
  providerName: ProQuest
Title Teat detection algorithm: YOLO vs. Haar-cascade
URI https://link.springer.com/article/10.1007/s12206-019-0339-5
https://www.proquest.com/docview/2481004909
https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002456065
Volume 33
WOSCitedRecordID wos000464749300039&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
ispartofPNX Journal of Mechanical Science and Technology, 2019, 33(4), , pp.1869-1874
journalDatabaseRights – providerCode: PRVPQU
  databaseName: Advanced Technologies & Aerospace Database
  customDbUrl:
  eissn: 1976-3824
  dateEnd: 20191231
  omitProxy: false
  ssIdentifier: ssj0062411
  issn: 1738-494X
  databaseCode: P5Z
  dateStart: 19970101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/hightechjournals
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Engineering Database
  customDbUrl:
  eissn: 1976-3824
  dateEnd: 20191231
  omitProxy: false
  ssIdentifier: ssj0062411
  issn: 1738-494X
  databaseCode: M7S
  dateStart: 19970101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl:
  eissn: 1976-3824
  dateEnd: 20191231
  omitProxy: false
  ssIdentifier: ssj0062411
  issn: 1738-494X
  databaseCode: BENPR
  dateStart: 19970101
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVAVX
  databaseName: Springer LINK
  customDbUrl:
  eissn: 1976-3824
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0062411
  issn: 1738-494X
  databaseCode: RSV
  dateStart: 19970101
  isFulltext: true
  titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22
  providerName: Springer Nature
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8QwEB58HfTgW1wfSxFPSrTbNG3iTUVRkHXRRVYvIU0TXdSutNXfbxJbV0UFvbSHpm34JvMIM5kPYFMLFsUGfWTJCVHINEVU-hhFJFFxkshAO-a5q7O43aa9HutU57iLutq9Tkk6Sz087BYEbvfLkI8xQ2QUxo23o5av4eLyqja_kXFJbpcVG00OWdirU5nffeKTMxrNcv0pzvySGnUe53jmX3OdhekqwPT231bEHIyobB6mPrQdXIDdrjHAXqpKV4aVeeLhdpD3y7vHPe_6_Ozceyl2vBMhciRFYcvnF6F7fNQ9PEEVcQKSmPglCkQcSaONwuAdtagINW0ZYUU4VpJhX2vq8nOpYgkjLNU6xmlCWBBpSpI0xUswlg0ytQxeYuI3AzFNmAotN7Xt7SJ9qZgIiMA0bIBfA8hl1VTccls88GE7ZAsFN1BwCwUnDdh6f-XpraPGb4M3jFT4vexz2wfb3m8H_D7nJto_5WFs6bVwA9ZqofFKAwsemJm6tCZrwHYtpOHjH_-48qfRqzAZOCnbUp41GCvzZ7UOE_Kl7Bd5E8YPjtqdi6YtKL001w65abrF-gr8PtvF
linkProvider Springer Nature
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1bb9MwFD7aCtLggcsuolAgQtvLJq-pnYuNhBACplYt7aRVU_dkOY49ppa0JKHTfhT_EdttKJu0ve2BpzwkcRyfL-eSc3w-gF0tWBSb1UeWnBAFTFNEpU9QFCYqThKJtWOeO-3F_T4djdjxGvyu9sLYsspKJzpFnU6l_UfexAFtuTQV-zj7iSxrlM2uVhQaC1h01dWlCdmKD50vRr57GB99HX5uoyWrAJIk9EuERRxJA1VhJhO1qAg0bZk3iUisJCO-1tQlr1LFEhayVOuYpEnIcKRpmKQpMcOuwwPjRWDmKgVPKsUfGWPo4rvY6JCABaMqiep26mHsQneGfEIYCq-ZwfUs19c83BtJWWfrjp7-Z6v0DJ4snWrv0-IreA5rKtuEx_-0WtyC5tAYHS9VpSs9yzwxOTfzLr__eO-dDXoDb14cem0hciRFYbcMbMPwPia8A7VsmqkX4CXGZ2XUpwlTgeXjtv1spC8VEzgUhAZ18CvRcblspG75PCZ81QLaSpsbaXMrbR7WYf_vLbNFF5G7Ln5n8MDH8oLb3t_2eD7l45ybCKfDg9hSipE6NCoA8KXWKfhK-nU4qCC0On3rE1_ePdhb2GgPv_V4r9PvvoJH2KHY1i41oFbmv9RreCjn5UWRv3Hfgwf8npH1B4i2QF0
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB71gRAcKE91oYUIwQVkNmvHsY1UVRVl1VVX2z2s0NKL5Th2W7VkS5K24qfx77C9CUuR6K0HTjkkcRzP5xmPZzwfwBurRMrc6CNPTogSYTniOiYopZlhWaaxDcxzX4ZsNOLTqRgvwc_2LIxPq2x1YlDU-Uz7PfIuTngvhKlE1zZpEePd_vb5d-QZpHyktaXTmENk3_y4cu5btTXYdbJ-i3H_8-TTHmoYBpAmNK4RVizVDrbKdSztcZVY3nN_lRJmtCCxtTwEsnIjMkFFbi0jeUYFTi2nWZ4T1-wyrDLnYvpswjE9bI1A6gxj8PWY0yeJSKZtQDWc2sM4uPECxYQIRK-ZxOWitNdWu38FaIPd66_9xyP2EB40i-1oZz47HsGSKR7D_T9KMD6B7sQZoyg3dUhJKyJ1duT6XR9_-xh9PRgeRJfVh2hPqRJpVfmjBE9hchsdfgYrxaww6xBlbi0reMwzYRLP0-3r3OhYG6EwVYQnHYhbMUrdFFj3PB9nclEa2kteOslLL3lJO_Du9yvn8-oiNz382mFDnuoT6WuC--vRTJ6W0nk-A5kwTzVGOrDRgkE22qiSCyR04H0Lp8Xtf37x-c2NvYK7DlByOBjtv4B7OADapzRtwEpdXphNuKMv65OqfBmmRgTyloH1C356STY
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=Teat+detection+algorithm%3A+YOLO+vs.+Haar-cascade&rft.jtitle=Journal+of+mechanical+science+and+technology&rft.au=Rastogi%2C+Akanksha&rft.au=Ryuh%2C+Beom+Sahng&rft.date=2019-04-01&rft.pub=Korean+Society+of+Mechanical+Engineers&rft.issn=1738-494X&rft.eissn=1976-3824&rft.volume=33&rft.issue=4&rft.spage=1869&rft.epage=1874&rft_id=info:doi/10.1007%2Fs12206-019-0339-5&rft.externalDocID=10_1007_s12206_019_0339_5
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1738-494X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1738-494X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1738-494X&client=summon