Related references
Note: Only part of the references are listed.Center and Scale Prediction: Anchor-free Approach for Pedestrian and Face Detection
Wei Liu et al.
PATTERN RECOGNITION (2023)
Effects of image data quality on a convolutional neural network trained in-tank fish detection model for recirculating aquaculture systems
Rakesh Ranjan et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2023)
Counting method for cultured fishes based on multi-modules and attention mechanism
Xiaoning Yu et al.
AQUACULTURAL ENGINEERING (2022)
Recent advances of deep learning algorithms for aquacultural machine vision systems with emphasis on fish
Daoliang Li et al.
ARTIFICIAL INTELLIGENCE REVIEW (2022)
Real-time detection and tracking of fish abnormal behavior based on improved YOLOV5 and SiamRPN plus
He Wang et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
Automatic, operational, high-resolution monitoring of fish length and catch numbers from landings using deep learning
Miquel Palmer et al.
FISHERIES RESEARCH (2022)
Nonintrusive and automatic quantitative analysis methods for fish behaviour in aquaculture
Jintao Liu et al.
AQUACULTURE RESEARCH (2022)
Pedestrian Detection for Autonomous Cars: Inference Fusion of Deep Neural Networks
Muhammad Mobaidul Islam et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2022)
Intelligent feeding technique based on predicting shrimp growth in recirculating aquaculture system
Fudi Chen et al.
AQUACULTURE RESEARCH (2022)
Application of intelligent and unmanned equipment in aquaculture: A review
Yinghao Wu et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
Non-contact weight estimation system for fish based on instance segmentation
Xiaoning Yu et al.
EXPERT SYSTEMS WITH APPLICATIONS (2022)
Robust detection of farmed fish by fusing YOLOv5 with DCM and ATM
Haiqing Li et al.
AQUACULTURAL ENGINEERING (2022)
A novel centerline extraction method for overlapping fish body length measurement in aquaculture images
Yun-peng Zhao et al.
AQUACULTURAL ENGINEERING (2022)
Underwater abnormal classification system based on deep learning: A case study on aquaculture fish farm in Taiwan
James C. Chen et al.
AQUACULTURAL ENGINEERING (2022)
Deep images enhancement for turbid underwater images based on unsupervised learning
Wen-Hui Zhou et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
Recent advances of target tracking applications in aquaculture with emphasis on fish
Yupeng Mei et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
Generative adversarial networks (GANs) for image augmentation in agriculture: A systematic review
Yuzhen Lu et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
Stepwise Domain Adaptation (SDA) for Object Detection in Autonomous Vehicles Using an Adaptive CenterNet
Guofa Li et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2022)
Water quality parameter analysis model based on fish behavior
Longqing Sun et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
LFCNet: A lightweight fish counting model based on density map regression
Yuanyang Zhao et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2022)
Application of computer vision in fish intelligent feeding system-A review
Dong An et al.
AQUACULTURE RESEARCH (2021)
Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review
Ling Yang et al.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2021)
Deep learning for smart fish farming: applications, opportunities and challenges
Xinting Yang et al.
REVIEWS IN AQUACULTURE (2021)
Automatic counting methods in aquaculture: A review
Daoliang Li et al.
JOURNAL OF THE WORLD AQUACULTURE SOCIETY (2021)
Multi-stream fish detection in unconstrained underwater videos by the fusion of two convolutional neural network detectors
Abdelouahid Ben Tamou et al.
APPLIED INTELLIGENCE (2021)
Multi-class fish stock statistics technology based on object classification and tracking algorithm
Tao Liu et al.
ECOLOGICAL INFORMATICS (2021)
Gliding Vertex on the Horizontal Bounding Box for Multi-Oriented Object Detection
Yongchao Xu et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2021)
Application of machine learning in intelligent fish aquaculture: A review
Shili Zhao et al.
AQUACULTURE (2021)
Real-time detection of uneaten feed pellets in underwater images for aquaculture using an improved YOLO-V4 network
Xuelong Hu et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)
Real-time nondestructive fish behavior detecting in mixed polyculture system using deep-learning and low-cost devices
Jun Hu et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Automatic Recognition of Fish Behavior with a Fusion of RGB and Optical Flow Data Based on Deep Learning
Guangxu Wang et al.
ANIMALS (2021)
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi et al.
JOURNAL OF BIG DATA (2021)
Automatic fish detection in underwater videos by a deep neural network-based hybrid motion learning system
Ahmad Salman et al.
ICES JOURNAL OF MARINE SCIENCE (2020)
Nonintrusive methods for biomass estimation in aquaculture with emphasis on fish: a review
Daoliang Li et al.
REVIEWS IN AQUACULTURE (2020)
Automatic segmentation of fish using deep learning with application to fish size measurement
Rafael Garcia et al.
ICES JOURNAL OF MARINE SCIENCE (2020)
Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia
Arthur F. A. Fernandes et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)
Fish freshness categorization from eyes and gills color features using multi-class artificial neural network and support vector machines
Hosna Mohammadi Lalabadi et al.
AQUACULTURAL ENGINEERING (2020)
Automating the Analysis of Fish Abundance Using Object Detection: Optimizing Animal Ecology With Deep Learning
Ellen M. Ditria et al.
FRONTIERS IN MARINE SCIENCE (2020)
Analysis of Behavior Trajectory Based on Deep Learning in Ammonia Environment for Fish
Wenkai Xu et al.
SENSORS (2020)
Simulation of Autonomous Underwater Vehicles (AUVs) Swarm Diffusion
Enrico Petritoli et al.
SENSORS (2020)
A modified YOLOv3 model for fish detection based on MobileNetv1 as backbone
Kewei Cai et al.
AQUACULTURAL ENGINEERING (2020)
MSR-YOLO: Method to Enhance Fish Detection and Tracking in Fish Farms
Hussam El-Din Mohamed et al.
11TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 3RD INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS (2020)
Fish Shoals Behavior Detection Based on Convolutional Neural Network and Spatiotemporal Information
Fangfang Han et al.
IEEE ACCESS (2020)
HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
Rajeev Ranjan et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2019)
Statistical performance of convex low-rank and sparse tensor recovery
Xiangrui Li et al.
PATTERN RECOGNITION (2019)
Evaluation of fish feeding intensity in aquaculture using a convolutional neural network and machine vision
Chao Zhou et al.
AQUACULTURE (2019)
Cascaded deep network systems with linked ensemble components for underwater fish detection in the wild
Alfonso B. Labao et al.
ECOLOGICAL INFORMATICS (2019)
Using machine vision to estimate fish length from images using regional convolutional neural networks
Graham G. Monkman et al.
METHODS IN ECOLOGY AND EVOLUTION (2019)
Object Detection With Deep Learning: A Review
Zhong-Qiu Zhao et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2019)
A spatio-temporal recurrent network for salmon feeding action recognition from underwater videos in aquaculture
Hakon Maloy et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)
Fish Detection and Tracking in Pisciculture Environment using Deep Instance Segmentation
C. S. Arvind et al.
PROCEEDINGS OF THE 2019 IEEE REGION 10 CONFERENCE (TENCON 2019): TECHNOLOGY, KNOWLEDGE, AND SOCIETY (2019)
A Comparative Study of State-of-the-Art Deep Learning Algorithms for Vehicle Detection
Hai Wang et al.
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE (2019)
Enhanced fish bending model for automatic tuna sizing using computer vision
P. Munoz-Benavent et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)
Arbitrary-Oriented Scene Text Detection via Rotation Proposals
Jianqi Ma et al.
IEEE TRANSACTIONS ON MULTIMEDIA (2018)
Three-dimensional location of target fish by monocular infrared imaging sensor based on a L-z correlation model
Kai Lin et al.
INFRARED PHYSICS & TECHNOLOGY (2018)
Deep visual domain adaptation: A survey
Mei Wang et al.
NEUROCOMPUTING (2018)
Automated Analysis of Marine Video With Limited Data
Deborah Levy et al.
PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2018)
Application of machine vision systems in aquaculture with emphasis on fish: state-of-the-art and key issues
Mohammadmehdi Saberioon et al.
REVIEWS IN AQUACULTURE (2017)
Biofloc technology application in aquaculture to support sustainable development goals
Peter Bossier et al.
MICROBIAL BIOTECHNOLOGY (2017)
Near-infrared imaging to quantify the feeding behavior of fish in aquaculture
Chao Zhou et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2017)
Mask R-CNN
Kaiming He et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)
Fish species classification in unconstrained underwater environments based on deep learning
Ahmad Salman et al.
LIMNOLOGY AND OCEANOGRAPHY-METHODS (2016)
Fish Locomotion: Recent Advances and New Directions
George V. Lauder
ANNUAL REVIEW OF MARINE SCIENCE, VOL 7 (2015)
Automated detection of rockfish in unconstrained underwater videos using Haar cascades and a new image dataset: labeled fishes in the wild
George Cutter et al.
2015 IEEE WINTER APPLICATIONS AND COMPUTER VISION WORKSHOPS (WACVW) (2015)
Fast R-CNN
Ross Girshick
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2015)
A dual camera system for counting and sizing Northern Bluefin Tuna (Thunnus thynnus; Linnaeus, 1758) stock, during transfer to aquaculture cages, with a semi automatic Artificial Neural Network tool
Corrado Costa et al.
AQUACULTURE (2009)
Automated measurement of species and length of fish by computer vision
D. J. White et al.
FISHERIES RESEARCH (2006)