Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners | Paper Citation Record

Observation 5f9e4fbd-9d41-4900-b72d-9b939c6358be · outbound

This paper cites The State of World Fisheries and Aquaculture 2024 – Blue Transformation in action.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners The State of World Fisheries and Aquaculture 2024 – Blue Transformation in action

Reference 1

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Observation 3db9c1c4-c73f-407c-8797-9125f5e6b36b · outbound

This paper cites Snapshot of the Large-Scale Tropical Tuna Purse Seine Fish- ing Fleets as of June 2024.International Seafood Sustainability Foundation, June 2024.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Snapshot of the Large-Scale Tropical Tuna Purse Seine Fish- ing Fleets as of June 2024.International Seafood Sustainability Foundation, June 2024

Reference 2

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Observation ee5147ad-8c4a-45c1-a291-297836e41d66 · outbound

This paper cites Griffiths, Valerie Allain, Simon D.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Griffiths, Valerie Allain, Simon D

Reference 3

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This paper cites Duparc, Pascal Cauquil, Mathieu Depetris, Patrice Dewals, Daniel Gaertner, A.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Duparc, Pascal Cauquil, Mathieu Depetris, Patrice Dewals, Daniel Gaertner, A

Reference 4

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

Reference 5

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This paper cites At-Sea Observing Using Video-Based Electronic Monitoring.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners At-Sea Observing Using Video-Based Electronic Monitoring

Reference 6

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Observation cc87fcca-dfb8-4203-80c4-2324da65ff4c · outbound

This paper cites Designing and Implementing Electronic Monitoring Systems for Fisheries: A Sup- plement to the Catch Share Design Manual.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Designing and Implementing Electronic Monitoring Systems for Fisheries: A Sup- plement to the Catch Share Design Manual

Reference 7

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

Reference 8

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Observation 2610f46e-a72b-4e7c-a4b5-5c89ab0927ac · outbound

This paper cites Comparing electronic monitoring system with ob- server data for estimating non-target species and discards on french tropical tuna purse seine vessels.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Comparing electronic monitoring system with ob- server data for estimating non-target species and discards on french tropical tuna purse seine vessels

Reference 9

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This paper cites Sabarros, Gwenaëlle Wain, An- toine Bonnieux, Sarah Le Couls, Romain Godefroy, Patrick Moëlo, Tiphaine Bet- tali, Michel Goujon, and Julien Lebranchu.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Sabarros, Gwenaëlle Wain, An- toine Bonnieux, Sarah Le Couls, Romain Godefroy, Patrick Moëlo, Tiphaine Bet- tali, Michel Goujon, and Julien Lebranchu

Reference 10

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Observation fbbe2159-d920-424d-9df8-939375bd4606 · outbound

This paper cites Increasing the functionalities and accuracy of fisheries electronic monitoring systems.Aquatic Conservation: Marine and Freshwater Ecosystems, 29(6):901–926, 2019.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Increasing the functionalities and accuracy of fisheries electronic monitoring systems.Aquatic Conservation: Marine and Freshwater Ecosystems, 29(6):901–926, 2019

Reference 11

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Observation 9290feb7-7218-4d3f-a3fb-d0d03c964ee2 · outbound

This paper cites Preliminary study about the suitability of an electronic monitoring system to record scientific and other information from the tropical tuna purse seine fishery.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Preliminary study about the suitability of an electronic monitoring system to record scientific and other information from the tropical tuna purse seine fishery

Reference 12

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Observation cfa5d202-8418-4a9b-bf33-5d77943dd6cb · outbound

This paper cites Murua, M.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Murua, M

Reference 13

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This paper cites Minimum Stan- dards for Electronic Monitoring Systems in Tropical Tuna Purse Seine and Long- line Fisheries.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Minimum Stan- dards for Electronic Monitoring Systems in Tropical Tuna Purse Seine and Long- line Fisheries

Reference 14

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

Reference 16

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Observation 343151b1-54f7-4a57-b35a-90b587f7fd0e · outbound

This paper cites Comments on the assessment of catch by species in the tropical purse seine fishery.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Comments on the assessment of catch by species in the tropical purse seine fishery

Reference 17

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This paper cites Fast freezing, slow tempering: The key to tuna (Thunnus albacares) quality retention.International Journal of Food Science and Technology, 59(5):3031– 3044, May 2024.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Fast freezing, slow tempering: The key to tuna (Thunnus albacares) quality retention.International Journal of Food Science and Technology, 59(5):3031– 3044, May 2024

Reference 18

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

Reference 19

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This paper cites Mask R-CNN.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Mask R-CNN

Reference 20

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Reference 21

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Observation 40c5f12a-7ffb-4ad4-88d8-5a370feeab94 · outbound

This paper cites Multi-stage image-based approach for fish detection and weight estimation.Biosystems Engineering, 257:104239, September 2025.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Multi-stage image-based approach for fish detection and weight estimation.Biosystems Engineering, 257:104239, September 2025

Reference 22

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This paper cites On the Opportunities and Risks of Foundation Models.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners On the Opportunities and Risks of Foundation Models

Reference 23

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This paper cites SAM2 for Image and Video Segmentation: A Comprehensive Survey.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners SAM2 for Image and Video Segmentation: A Comprehensive Survey

Reference 24

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners DINOv2: Learning Robust Visual Features without Supervision

Reference 25

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners SAM 2: Segment Anything in Images and Videos

Reference 26

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This paper cites Training- free fish species population monitoring in unconstrained underwater videos.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Training- free fish species population monitoring in unconstrained underwater videos

Reference 27

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Evaluation of Segment Anything Model 2: The Role of SAM2 in the Underwater Environment

Reference 28

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This paper cites Advancing Fisheries Re- search and Management with Computer Vision: A Survey of Recent Develop- ments and Pending Challenges.Fishes, 10(2):74, February 2025.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Advancing Fisheries Re- search and Management with Computer Vision: A Survey of Recent Develop- ments and Pending Challenges.Fishes, 10(2):74, February 2025

Reference 29

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Fernandes

Reference 30

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners ai Corporation

Reference 31

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Bett, Andrew R

Reference 32

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners ASFIS List of Species for Fishery Statistics Purposes

Reference 33

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This paper cites YOLOv9: Learning What Y ou Want to Learn Using Programmable Gradient Information, February.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners YOLOv9: Learning What Y ou Want to Learn Using Programmable Gradient Information, February

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This paper cites DINOSim: Zero-Shot Object Detection and Semantic Segmentation on Electron Microscopy Images, March 2025.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners DINOSim: Zero-Shot Object Detection and Semantic Segmentation on Electron Microscopy Images, March 2025

Reference 35

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 36

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Faster R-CNN: To- wards Real-Time Object Detection with Region Proposal Networks.IEEE Trans- actions on Pattern Analysis and Machine Intelligence, 39(6):1137–1149, June

Reference 37

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Simple Online and Realtime Tracking

Reference 38

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Simple Online and Realtime Tracking with a Deep Association Metric

Reference 39

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners ByteTrack: Multi-object Tracking by Associating Every Detection Box

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

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This paper cites Dynamic Target Tracking and Fol- lowing with UAVs Using Multi-Target Information: Leveraging YOLOv8 and MOT Algorithms.DRONES, 8(9):488, September 2024.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Dynamic Target Tracking and Fol- lowing with UAVs Using Multi-Target Information: Leveraging YOLOv8 and MOT Algorithms.DRONES, 8(9):488, September 2024

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Designing Network Design Spaces

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Mujtaba and Nihar R

Reference 45

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Ackland, David M

Reference 46

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Shepherd, Juliet A

Reference 47

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Culverhouse, Robert Williams, Beatriz Reguera, Vincent Herry, and Son- soles González-Gil

Reference 48

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Culverhouse

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Austen, Markus Bindemann, Richard A

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Foundation Models

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This paper cites The Fishnet Open Images Database: A Dataset for Fish Detection and Fine-Grained Categorization in Fisheries.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners The Fishnet Open Images Database: A Dataset for Fish Detection and Fine-Grained Categorization in Fisheries

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

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This paper cites RSNC-YOLO: A Deep-Learning-Based Method for Automatic Fine-Grained Tuna Recognition in Complex Environments.Applied Sciences, 14 (22):10732, January 2024.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners RSNC-YOLO: A Deep-Learning-Based Method for Automatic Fine-Grained Tuna Recognition in Complex Environments.Applied Sciences, 14 (22):10732, January 2024

Reference 54

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Observation 512f5e80-f173-4e56-8e84-5c46e7d39083 · outbound

This paper cites Live Weight Prediction of Cattle Based on Deep Re- gression of RGB-D Images.Agriculture, 12(11):1794, November 2022.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Live Weight Prediction of Cattle Based on Deep Re- gression of RGB-D Images.Agriculture, 12(11):1794, November 2022

Reference 55

Resolution: verified exact; doi, observed 2026-08-04T06:53:26.599194Z

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Observation d2eea436-299c-4a46-95be-7abb2147c894 · outbound

This paper cites A brief survey on RGB-D semantic segmentation using deep learning.Displays, 70:102080, December 2021.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners A brief survey on RGB-D semantic segmentation using deep learning.Displays, 70:102080, December 2021

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-04T06:49:06.266077Z

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Observation 04a67cc9-b3d5-4bc0-bbfb-1c2a53cf71f2 · outbound

This paper cites International Commission for the Conservation of Atlantic Tuna, 2006.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners International Commission for the Conservation of Atlantic Tuna, 2006

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-04T06:49:06.377477Z

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Observation 6d040576-af86-4024-be01-c5ca1c2490b2 · outbound

This paper cites Fernandes-Salvador, Nicolas Goñi, Igor Granado, Iñaki Quincoces, Leire Ibaibarriaga, Jon Ruiz, Hilario Murua, and Ainhoa Caballero.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Fernandes-Salvador, Nicolas Goñi, Igor Granado, Iñaki Quincoces, Leire Ibaibarriaga, Jon Ruiz, Hilario Murua, and Ainhoa Caballero

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T06:49:06.474028Z

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Observation 97beea04-007f-4f4c-8df9-5422b23468b0 · outbound

This paper cites Global habitat preferences of commercially valuable tuna.Deep Sea Research Part II: Topical Studies in Oceanography, 113:102–112, March 2015.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Global habitat preferences of commercially valuable tuna.Deep Sea Research Part II: Topical Studies in Oceanography, 113:102–112, March 2015

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-04T06:49:06.544274Z

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Observation fd5eea3c-465c-4bb1-8d94-047c8852c4ae · outbound

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Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

Reference 645

Resolution: verified exact; doi, observed 2026-08-04T06:53:26.553931Z

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Observation 35eb1d06-6ecd-4cfb-ac8f-82dce53dc0d1 · outbound

This paper cites doi:10.1109/TPAMI.2016.2577031.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners doi:10.1109/TPAMI.2016.2577031

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-04T06:49:04.098795Z

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Observation fe646559-1b5b-49e5-b32f-f812a4a2fc11 · outbound

This paper cites YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T06:49:03.692113Z

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Observation 904391a0-8854-4e27-b362-af21d25c4830 · outbound

This paper cites Number: 2 Publisher: Multidisciplinary Digi- tal Publishing Institute.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Number: 2 Publisher: Multidisciplinary Digi- tal Publishing Institute

Reference 3888

Resolution: verified exact; doi, observed 2026-08-04T06:53:27.229416Z

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Observation fc2328a9-72e9-4c4b-82f5-cdf0b6567a15 · outbound

This paper cites an unresolved cited work.

Deep Learning for Accurate Vision-based Catch Composition in Tropical Tuna Purse Seiners Unresolved cited work

Reference 5110

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