A novel automatic detection method for breeding behavior of broodstock based on improved YOLOv5

A lightweight dead fish detection method based on deformable convolution and YOLOV4

(2022) Shili Zhao et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Fast detection of cannibalism behavior of juvenile fish based on deep learning

(2022) He Wang et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A novel automatic detection method for abnormal behavior of single fish using image fusion

(2022) Xin Li et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Real-time detection of uneaten feed pellets in underwater images for aquaculture using an improved YOLO-V4 network

(2021) Xuelong Hu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Identification methodology of special behaviors for fish school based on spatial behavior characteristics

(2021) Xiaoning Yu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Behavior evaluation of rainbow trout (Oncorhynchus mykiss) following temperature and ammonia alterations

(2021) Ahmad Mohamadi Yalsuyi et al.   ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY

Real-time nondestructive fish behavior detecting in mixed polyculture system using deep-learning and low-cost devices

(2021) Jun Hu et al.   EXPERT SYSTEMS WITH APPLICATIONS

Channel pruned YOLO V5s-based deep learning approach for rapid and accurate apple fruitlet detection before fruit thinning

(2021) Dandan Wang et al.   BIOSYSTEMS ENGINEERING

Analysis of Behavior Trajectory Based on Deep Learning in Ammonia Environment for Fish

(2020) Wenkai Xu et al.   SENSORS

Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review

(2020) Ling Yang et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

A spatio-temporal recurrent network for salmon feeding action recognition from underwater videos in aquaculture

(2019) Håkon Måløy et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Modified motion influence map and recurrent neural network-based monitoring of the local unusual behaviors for fish school in intensive aquaculture

(2018) Jian Zhao et al.   AQUACULTURE

Robust tracking of fish schools using CNN for head identification

(2016) Shuo Hong Wang et al.   MULTIMEDIA TOOLS AND APPLICATIONS

A computer vision system to analyse the swimming behaviour of farmed fish in commercial aquaculture facilities: A case study using cage-held Atlantic salmon

(2011) T.H. Pinkiewicz et al.   AQUACULTURAL ENGINEERING