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

An attribution-based pruning method for real-time mango detection with YOLO network

(2020) Rui Shi et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Intelligent monitoring and control technologies of open sea cage culture: A review

(2020) Yaoguang Wei et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia

(2020) Arthur F.A. Fernandes et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Automatic Fish Population Counting by Machine Vision and a Hybrid Deep Neural Network Model

(2020) Song Zhang et al.   Animals

Effects of antioxidant supplementation (nano‑selenium, vitamin C and E) on growth performance, blood biochemistry, immune status and body composition of rainbow trout (Oncorhynchus mykiss) under sub-lethal ammonia exposure

(2020) Mohammad Harsij et al.   AQUACULTURE

Deep learning for smart fish farming: applications, opportunities and challenges

(2020) Xinting Yang et al.   Reviews in Aquaculture

Apple detection during different growth stages in orchards using the improved YOLO-V3 model

(2019) Yunong Tian et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Growth performance, physiological response and histology changes of juvenile blunt snout bream, Megalobrama amblycephala exposed to chronic ammonia

(2019) Wuxiao Zhang et al.   AQUACULTURE

Cascaded deep network systems with linked ensemble components for underwater fish detection in the wild

(2019) Alfonso B. Labao et al.   Ecological Informatics

Integration of sonar and optical camera images using deep neural network for fish monitoring

(2019) Kei Terayama et al.   AQUACULTURAL 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

Visual features based automated identification of fish species using deep convolutional neural networks

(2019) Hafiz Tayyab Rauf et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Intelligent feeding control methods in aquaculture with an emphasis on fish: a review

(2017) Chao Zhou et al.   Reviews in Aquaculture

Improving feed efficiency in fish using selective breeding: a review

(2017) Hugues de Verdal et al.   Reviews in Aquaculture

Modelling growth performance and feeding behaviour of Atlantic salmon ( Salmo salar L.) in commercial-size aquaculture net pens: Model details and validation through full-scale experiments

(2016) Martin Føre et al.   AQUACULTURE

Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior

(2016) Chong-Yi Li et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Development of an adaptive neural-based fuzzy inference system for feeding decision-making assessment in silver perch ( Bidyanus bidyanus ) culture

(2015) Te-Hui Wu et al.   AQUACULTURAL ENGINEERING

Automatic Feeding Control for Dense Aquaculture Fish Tanks

(2015) Yousef Atoum et al.   IEEE SIGNAL PROCESSING LETTERS

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

(2015) Kaiming He et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Deep learning

(2015) Yann LeCun et al.   NATURE

Measuring feeding activity of fish in RAS using computer vision

(2014) Ziyi Liu et al.   AQUACULTURAL ENGINEERING

Fish protein hydrolysates: Proximate composition, amino acid composition, antioxidant activities and applications: A review

(2012) M. Chalamaiah et al.   FOOD CHEMISTRY

Development of two telemetry-based systems for monitoring the feeding behaviour of Atlantic salmon (Salmo salar L.) in aquaculture sea-cages

(2011) Martin Føre et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Underwater Image Enhancement by Wavelength Compensation and Dehazing

(2011) J. Y. Chiang et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Automated acoustic method for counting and sizing farmed fish during transfer using DIDSON

(2009) Jun Han et al.   FISHERIES SCIENCE