Fishing Gear Pattern Recognition by Including Supervised Autoencoder Dimensional Reduction

Fishing is a crucial worldwide activity as it provides a source of food and economic income. A challenge in ecology and conservation is decreasing overfishing and illegal, unreported, and unregulated fishing (IUUF). One strategy to decrease those issues is to track vessels for detecting fishing beha...

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Published in:IEEE geoscience and remote sensing letters Vol. 19; pp. 1 - 5
Main Authors: Carlos, Hugo, Aranda, Ramon, Velasco, Mariana Rivera-De, Rodriguez-Gonzalez, Ansel Y., Mendez-Lopez, Maria Elena
Format: Journal Article
Language:English
Published: Piscataway IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Artificial intelligence
Centroids
Coders
Conservation
Data analysis
Data processing
Dimension reduction
Ecology
Economics
Fisheries
Fisheries management
Fishery management
Fishing
Fishing equipment
Fishing gear
Food sources
Gears
Illegal fishing
Longline fishing
Marine vehicles
Monitoring
Overfishing
Pattern recognition
Proposals
Purse seines
supervised autoencoder
Support vector machines
Trajectory
vessel behavior
Vessels
ISSN:1545-598X, 1558-0571
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Abstract Fishing is a crucial worldwide activity as it provides a source of food and economic income. A challenge in ecology and conservation is decreasing overfishing and illegal, unreported, and unregulated fishing (IUUF). One strategy to decrease those issues is to track vessels for detecting fishing behaviors through monitory systems. In this letter, we present an approach to classify fishing behaviors, specifically, for four fishing gear types (trawl, purse seine, fixed gear, and longline) using automatic identification systems (AISs) data from the Global Fishing Watch platform. Thus, our main contribution is how we propose data processing by including a supervised autoencoder dimensional reduction (SA-DR) processing data step. This step allows removing redundant features and noise, avoiding overfitting, decreasing data complexity, and preserving the differences between classes. Specifically, we propose to use IVIS and centroid encoder (CE) methods. The experimental results show how our approach applying SA-DR over the vessel trajectory feature representation reduces the variation results among different classifiers and achieves a high classification accuracy of up to 95%. This result could help prevent IUUF, overfishing, and improve fishery management strategies.
AbstractList Fishing is a crucial worldwide activity as it provides a source of food and economic income. A challenge in ecology and conservation is decreasing overfishing and illegal, unreported, and unregulated fishing (IUUF). One strategy to decrease those issues is to track vessels for detecting fishing behaviors through monitory systems. In this letter, we present an approach to classify fishing behaviors, specifically, for four fishing gear types (trawl, purse seine, fixed gear, and longline) using automatic identification systems (AISs) data from the Global Fishing Watch platform. Thus, our main contribution is how we propose data processing by including a supervised autoencoder dimensional reduction (SA-DR) processing data step. This step allows removing redundant features and noise, avoiding overfitting, decreasing data complexity, and preserving the differences between classes. Specifically, we propose to use IVIS and centroid encoder (CE) methods. The experimental results show how our approach applying SA-DR over the vessel trajectory feature representation reduces the variation results among different classifiers and achieves a high classification accuracy of up to 95%. This result could help prevent IUUF, overfishing, and improve fishery management strategies.
Author Velasco, Mariana Rivera-De
Mendez-Lopez, Maria Elena
Rodriguez-Gonzalez, Ansel Y.
Aranda, Ramon
Carlos, Hugo
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Cites_doi 10.3390/s20133782
10.1037/h0070888
10.1016/j.marpol.2018.04.023
10.35940/ijrte.b1067.0782s619
10.1145/3369555.3369574
10.1139/cjfas-2013-0572
10.1007/978-3-030-44267-5_20
10.1080/14786440109462720
10.3389/fmars.2020.589000
10.1126/science.290.5500.2319
10.1002/aic.690370209
10.1016/j.marpol.2020.103980
10.1016/j.marpol.2018.08.003
10.1198/016214505000000628
10.1007/bf02288916
10.3390/w11020213
10.3390/app10114010
10.1109/JOE.2017.2723278
10.1162/neco.2007.19.9.2536
10.1371/journal.pone.0163760
10.1007/s11277-020-07200-w
10.1111/j.1469-1809.1936.tb02137.x
10.1016/j.fishres.2007.08.007
10.21105/joss.00861
10.1016/B978-0-12-817945-1.00015-0
10.1007/s11042-020-08949-9
10.1002/fee.2147
10.1007/s00773-019-00694-5
10.1162/089976603321780317
10.3390/rs12040702
10.1007/bf00337288
10.1016/j.patcog.2011.12.006
10.1093/icesjms/fsx230
10.1145/1015330.1015345
10.1038/s41598-019-45301-0
10.1016/j.patrec.2009.05.011
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References ref13
ref35
ref12
ref15
ref37
ref14
ref36
ref31
Ghosh (ref40) 2020
ref30
ref11
ref33
ref10
ref32
Snoek (ref42)
ref2
ref1
ref17
ref39
ref16
Song (ref34)
ref38
ref19
ref18
ref24
ref23
ref26
ref25
ref20
(ref22) 2021
ref21
ref43
ref28
(ref3) 2020
ref27
ref29
ref8
ref7
ref4
ref6
Borit (ref9) 2020
ref5
Hermans (ref41) 2017
References_xml – start-page: 1385
  volume-title: Proc. 20th Int. Conf. Neural Inf. Process. Syst.
  ident: ref34
  article-title: Colored maximum variance unfolding
– ident: ref16
  doi: 10.3390/s20133782
– ident: ref26
  doi: 10.1037/h0070888
– ident: ref1
  doi: 10.1016/j.marpol.2018.04.023
– ident: ref12
  doi: 10.35940/ijrte.b1067.0782s619
– ident: ref18
  doi: 10.1145/3369555.3369574
– ident: ref24
  doi: 10.1139/cjfas-2013-0572
– ident: ref19
  doi: 10.1007/978-3-030-44267-5_20
– ident: ref25
  doi: 10.1080/14786440109462720
– ident: ref4
  doi: 10.3389/fmars.2020.589000
– year: 2017
  ident: ref41
  article-title: In defense of the triplet loss for person re-identification
  publication-title: arXiv:1703.07737
– ident: ref29
  doi: 10.1126/science.290.5500.2319
– ident: ref38
  doi: 10.1002/aic.690370209
– ident: ref5
  doi: 10.1016/j.marpol.2020.103980
– ident: ref8
  doi: 10.1016/j.marpol.2018.08.003
– ident: ref33
  doi: 10.1198/016214505000000628
– ident: ref28
  doi: 10.1007/bf02288916
– year: 2020
  ident: ref40
  article-title: Supervised dimensionality reduction and visualization using centroid-encoder
  publication-title: arXiv:2002.11934
– ident: ref6
  doi: 10.3390/w11020213
– ident: ref13
  doi: 10.3390/app10114010
– ident: ref17
  doi: 10.1109/JOE.2017.2723278
– ident: ref35
  doi: 10.1162/neco.2007.19.9.2536
– ident: ref11
  doi: 10.1371/journal.pone.0163760
– ident: ref14
  doi: 10.1007/s11277-020-07200-w
– ident: ref32
  doi: 10.1111/j.1469-1809.1936.tb02137.x
– ident: ref23
  doi: 10.1016/j.fishres.2007.08.007
– ident: ref43
  doi: 10.21105/joss.00861
– start-page: 2951
  volume-title: Proc. NIPS
  ident: ref42
  article-title: Practical Bayesian optimization of machine learning algorithms
– ident: ref2
  doi: 10.1016/B978-0-12-817945-1.00015-0
– ident: ref21
  doi: 10.1007/s11042-020-08949-9
– ident: ref7
  doi: 10.1002/fee.2147
– ident: ref20
  doi: 10.1007/s00773-019-00694-5
– ident: ref30
  doi: 10.1162/089976603321780317
– ident: ref15
  doi: 10.3390/rs12040702
– ident: ref27
  doi: 10.1007/bf00337288
– ident: ref37
  doi: 10.1016/j.patcog.2011.12.006
– ident: ref10
  doi: 10.1093/icesjms/fsx230
– volume-title: FAO Yearbook of Fishery and Aquaculture Statistics
  year: 2020
  ident: ref3
– ident: ref31
  doi: 10.1145/1015330.1015345
– ident: ref39
  doi: 10.1038/s41598-019-45301-0
– volume-title: FAO Fisheries and Aquaculture Circular No. 1197
  year: 2020
  ident: ref9
  article-title: Beyond regulatory compliance—Seafood traceability benefits and success cases
– volume-title: Fishing Gear Types. Bottom Trawls. Technology Fact Sheets
  year: 2021
  ident: ref22
– ident: ref36
  doi: 10.1016/j.patrec.2009.05.011
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Snippet Fishing is a crucial worldwide activity as it provides a source of food and economic income. A challenge in ecology and conservation is decreasing overfishing...
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SubjectTerms Artificial intelligence
Centroids
Coders
Conservation
Data analysis
Data processing
Dimension reduction
Ecology
Economics
Fisheries
Fisheries management
Fishery management
Fishing
Fishing equipment
Fishing gear
Food sources
Gears
Illegal fishing
Longline fishing
Marine vehicles
Monitoring
Overfishing
Pattern recognition
Proposals
Purse seines
supervised autoencoder
Support vector machines
Trajectory
vessel behavior
Vessels
Title Fishing Gear Pattern Recognition by Including Supervised Autoencoder Dimensional Reduction
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