Aquaculture

Latest papers

10 papers0 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

OceanTensorCube and ST-MMT: A Multimodal Data and Transformer System for Seven-Day Forecasting of Pyropia Bleaching
Oct 19, 2026Gwangjin Kim, Cheolyoung Jang, Yosep JoTime Series Forecasting Spatiotemporal Forecasting
NCS Instructor, Smart Human Resources Development Institute, Republic of Korea · NH Networks LLC, Republic of Korea · DreamTech Co., Ltd., Republic of Korea
Enhancing Shrimp Disease Detection via Deep Learning and Data Refinement for Resilient Aquaculture
Sep 20, 2026Vinh Canh-Thanh Truong, Hai-Binh Pham, Ngoc Hong TranAquaculture
Computer Science Program Vietnamese-German University Ho Chi Minh City, Vietnam
Machine Learning in Fish Farming
Sep 12, 2026Fearghal O'Donncha, Nikos Papandroulakis, Jennie Korus +10Aquaculture
IBM Research Europe, Dublin, Ireland · Hellenic Centre for Marine Research, Crete, Greece · Innovasea Marine Systems Canada, Nova Scotia, Canada +6
Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture
Jul 10, 2026Rakesh Ranjan, Gajanan S. Kothawade, Kata Sharrer +2Edge Inference You Only Look Once
The Conservation Fund Freshwater Institute, Shepherdstown, WV, 25443
Automated 3D Kinematic Monitoring for Circadian Activity and Anomaly Detection in Juvenile Fish
Jun 5, 2026Chih-Wei Huang, Chang-Wen Huang, Chung-Ping Chiang +1Aquaculture Anomaly Detection
AI Research Center, National Taiwan Ocean Univ., Keelung City 20224, Taiwan. · Dept. of Aquaculture, National Taiwan Ocean Univ., Keelung City 20224, Taiwan. · Center of Excellence for the Oceans, National Taiwan Ocean University, Keelung City 20224, Taiwan.
A Novel Computer Vision Approach for Assessing Fish Responses to Intrusive Objects in Aquaculture
May 28, 2026Hanne-Grete Alvheim, Stian Mjelde Jakobsen, Martin Føre +1Stereo Vision Aquaculture
Department of Engineering Cybernetics, NTNU · Department of Aquaculture, SINTEF Ocean AS
Patch Ensembles for Robust Salmon Re-Identification with Weak Trajectory Labels
May 18, 2026Espen Uri Høgstedt, Christian Schellewald, Annette Stahl +1Biometric Identification Animal Re-Identification
Department of Computer Science, Norwegian University of Science and Technology, Norway · SINTEF Ocean, Norway · Department of Engineering Cybernetics, Norwegian University of Science and Technology, Norway
Video-based Locomotion Analysis for Fish Health Monitoring
Mar 5, 2026Timon Palm, Clemens Seibold, Anna Hilsmann +1Aquaculture Animal Behavior Analysis
Fraunhofer HHI, Berlin, Germany · Humboldt University of Berlin, Berlin, Germany
FinSight-Net:A Physics-Aware Decoupled Network with Frequency-Domain Compensation for Underwater Fish Detection in Smart Aquaculture
Feb 23, 2026Jinsong Yang, Zeyuan Hu, Yichen Li +1Underwater Object Detection Efficient Object Detection
Dalian Key Laboratory of Smart Fishery, Dalian, China · College of Information Engineering, Dalian Ocean University, China · Liaoning Provincial Key of Marine Information Technology, China +2
An interpretable framework using foundation models for fish sex identification
Feb 22, 2026Zheng Miao, Tien-Chieh HungAquaculture Explainable Image Classification
Department of Biological and Agricultural Engineering, University of California Davis, 1 Shields Ave., Davis, CA 95616, USA

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OceanTensorCube and ST-MMT: A Multimodal Data and Transformer System for Seven-Day Forecasting of Pyropia Bleaching

Gwangjin Kim, Cheolyoung Jang, Yosep Jo

NCS Instructor, Smart Human Resources Development Institute, Republic of Korea · NH Networks LLC, Republic of Korea · DreamTech Co., Ltd., Republic of Korea

Time Series Forecasting Spatiotemporal Forecasting Aquaculture Multivariate Time Series Forecasting Spatiotemporal Transformers

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Bleaching of cultured Pyropia (laver) causes losses in Korean seaweed farming. We present a system that forecasts bleaching seven days ahead for farm clusters. OceanTensorCube aligns 32 channels from public marine, meteorological, ocean-model and satellite sources on a 30 m grid, and ST-MMT, a 9.2-million-parameter spatiotemporal transformer with hub-style multi-head cross-attention between variable groups, maps a 14-day input window to a seven-day-ahead bleaching probability. On the validation set, a six-seed ensemble detects every reported positive at a false-alarm rate of at most 3.5%, an upper bound because the report-based labels are positive-unlabeled. A same-date control on separately trained models indicates that the architecture discriminates between clusters when the calendar is held fixed. We also report the system's weaknesses: skill falls steeply as the quarterly nutrient survey ages (ROC-AUC 0.94 at 30 days, 0.53 at 129 days), and a single LSTM on cluster-average series outperforms a single ST-MMT, with only the ensemble leading at the operating point. We describe the labeling procedure, the evaluation protocol and the operational gate that withholds forecasts when inputs are stale. The forecasting service is operated at https://oceantensor.ai.kr.