Deep learning for smart fish farming: applications, opportunities and challenges
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Deep learning for smart fish farming: applications, opportunities and challenges
Authors
Keywords
-
Journal
Reviews in Aquaculture
Volume -, Issue -, Pages -
Publisher
Wiley
Online
2020-06-30
DOI
10.1111/raq.12464
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- 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
- Deep learning-based appearance features extraction for automated carp species identification
- (2020) Ashkan Banan et al. AQUACULTURAL ENGINEERING
- Real-time robust detector for underwater live crabs based on deep learning
- (2020) Shuo Cao et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Fish detection and species classification in underwater environments using deep learning with temporal information
- (2020) Ahsan Jalal et al. Ecological Informatics
- Research of dissolved oxygen prediction in recirculating aquaculture systems based on deep belief network
- (2020) Qin Ren et al. AQUACULTURAL ENGINEERING
- idtracker.ai: tracking all individuals in small or large collectives of unmarked animals
- (2019) Francisco Romero-Ferrero et al. NATURE METHODS
- A Water Quality Prediction Method Based on the Deep LSTM Network Considering Correlation in Smart Mariculture
- (2019) Zhuhua Hu et al. SENSORS
- Automatic fish detection in underwater videos by a deep neural network-based hybrid motion learning system
- (2019) Ahmad Salman et al. ICES JOURNAL OF MARINE SCIENCE
- Opportunities to improve fisheries management through innovative technology and advanced data systems
- (2019) Darcy Bradley et al. FISH AND FISHERIES
- Interactions and management for the future of marine aquaculture and capture fisheries
- (2019) Tyler Clavelle et al. FISH AND FISHERIES
- Evaluation of fish feeding intensity in aquaculture using a convolutional neural network and machine vision
- (2019) Chao Zhou et al. AQUACULTURE
- Unlocking the potential of ancient fish DNA in the genomic era
- (2019) Tom Oosting et al. Evolutionary Applications
- Cascaded deep network systems with linked ensemble components for underwater fish detection in the wild
- (2019) Alfonso B. Labao et al. Ecological Informatics
- Identifying the species of harvested tuna and billfish using deep convolutional neural networks
- (2019) Yi-Chin Lu et al. ICES JOURNAL OF MARINE SCIENCE
- Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction
- (2019) Chinmay Belthangady et al. NATURE METHODS
- Integration of sonar and optical camera images using deep neural network for fish monitoring
- (2019) Kei Terayama et al. AQUACULTURAL ENGINEERING
- Improving Pantanal fish species recognition through taxonomic ranks in convolutional neural networks
- (2019) Anderson Aparecido dos Santos et al. Ecological Informatics
- Subsurface velocity inversion from deep learning-based data assimilation
- (2019) Bo Mao et al. JOURNAL OF APPLIED GEOPHYSICS
- Attention-based recurrent neural networks for accurate short-term and long-term dissolved oxygen prediction
- (2019) Yeqi Liu et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Digital camera monitoring of recreational fishing effort: Applications and challenges
- (2019) Bruce W. Hartill et al. FISH AND FISHERIES
- Automatic detection of Western rock lobster using synthetic data
- (2019) Ammar Mahmood et al. ICES JOURNAL OF MARINE SCIENCE
- Image-based, unsupervised estimation of fish size from commercial landings using deep learning
- (2019) Amaya Álvarez-Ellacuría et al. ICES JOURNAL OF MARINE SCIENCE
- Automatic measurement of the body length of harvested fish using convolutional neural networks
- (2019) Chi-Hsuan Tseng et al. BIOSYSTEMS 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
- Automatic live fingerlings counting using computer vision
- (2019) Pedro Lucas França Albuquerque 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
- Automated within tank fish mass estimation using infrared reflection system
- (2018) Mohammadmehdi Saberioon et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Near infrared computer vision and neuro-fuzzy model-based feeding decision system for fish in aquaculture
- (2018) Chao Zhou et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep learning in agriculture: A survey
- (2018) Andreas Kamilaris et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Research on a dissolved oxygen prediction method for recirculating aquaculture systems based on a convolution neural network
- (2018) Xuxiang Ta et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- SIFT Meets CNN: A Decade Survey of Instance Retrieval
- (2018) Liang Zheng et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Deep learning for smart manufacturing: Methods and applications
- (2018) Jinjiang Wang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Transferring deep knowledge for object recognition in Low-quality underwater videos
- (2018) Xin Sun et al. NEUROCOMPUTING
- Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success
- (2018) James H. Thrall et al. Journal of the American College of Radiology
- Visual interpretability for deep learning: a survey
- (2018) Quan-shi Zhang et al. Frontiers of Information Technology & Electronic Engineering
- Underwater-Drone With Panoramic Camera for Automatic Fish Recognition Based on Deep Learning
- (2018) Lin Meng et al. IEEE Access
- Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review
- (2018) Diego Inácio Patrício et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A Deep learning method for accurate and fast identification of coral reef fishes in underwater images
- (2018) Sébastien Villon et al. Ecological Informatics
- OUP accepted manuscript
- (2018) ICES JOURNAL OF MARINE SCIENCE
- Automatic classification of grouper species by their sounds using deep neural networks
- (2018) Ali K. Ibrahim et al. JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
- Machine Learning in Agriculture: A Review
- (2018) Konstantinos Liakos et al. SENSORS
- Tracking Fish Abundance by Underwater Image Recognition
- (2018) Simone Marini et al. Scientific Reports
- Design and Implementation of an Assistive Real-Time Red Lionfish Detection System for AUV/ROVs
- (2018) M-Mahdi Naddaf-Sh et al. COMPLEXITY
- Feeding behavior recognition for group-housed pigs with the Faster R-CNN
- (2018) Qiumei Yang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A review of state-of-the-art techniques for abnormal human activity recognition
- (2018) Chhavi Dhiman et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Image annotation: Then and now
- (2018) P.K. Bhagat et al. IMAGE AND VISION COMPUTING
- Automatic interpretation of otoliths using deep learning
- (2018) Endre Moen et al. PLoS One
- Automatic fish species classification in underwater videos: exploiting pre-trained deep neural network models to compensate for limited labelled data
- (2017) Shoaib Ahmed Siddiqui et al. ICES JOURNAL OF MARINE SCIENCE
- Geometric Deep Learning: Going beyond Euclidean data
- (2017) Michael M. Bronstein et al. IEEE SIGNAL PROCESSING MAGAZINE
- Toolkits and Libraries for Deep Learning
- (2017) Bradley J. Erickson et al. JOURNAL OF DIGITAL IMAGING
- Using stereoscopic video cameras to evaluate seagrass meadows nursery function in the Mediterranean
- (2017) Carlos Díaz-Gil et al. MARINE BIOLOGY
- A survey on deep learning in medical image analysis
- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- Brain Intelligence: Go beyond Artificial Intelligence
- (2017) Huimin Lu et al. MOBILE NETWORKS & APPLICATIONS
- Learning cast shadow appearance for human posture recognition
- (2017) Rafik Gouiaa et al. PATTERN RECOGNITION LETTERS
- 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
- An adaptive image enhancement method for a recirculating aquaculture system
- (2017) Chao Zhou et al. Scientific Reports
- Deep Learning for Health Informatics
- (2017) Daniele Ravi et al. IEEE Journal of Biomedical and Health Informatics
- Deep learning for natural language processing: advantages and challenges
- (2017) Hang Li National Science Review
- A comparative analysis among computational intelligence techniques for dissolved oxygen prediction in Delaware River
- (2017) Ehsan Olyaie et al. Geoscience Frontiers
- Zebrafish tracking using convolutional neural networks
- (2017) Zhiping XU et al. Scientific Reports
- Deep vs. shallow networks: An approximation theory perspective
- (2016) H. N. Mhaskar et al. Analysis and Applications
- 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
- Models for estimating feed intake in aquaculture: A review
- (2016) Min Sun et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Image-Based Monitoring of Jellyfish Using Deep Learning Architecture
- (2016) Hanguen Kim et al. IEEE SENSORS JOURNAL
- Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
- (2016) Varun Gulshan et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Robust tracking of fish schools using CNN for head identification
- (2016) Shuo Hong Wang et al. MULTIMEDIA TOOLS AND APPLICATIONS
- DeepFish: Accurate underwater live fish recognition with a deep architecture
- (2016) Hongwei Qin et al. NEUROCOMPUTING
- Fisheries management impacts on target species status
- (2016) Michael C. Melnychuk et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Stock assessment in inland fisheries: a foundation for sustainable use and conservation
- (2016) K. Lorenzen et al. REVIEWS IN FISH BIOLOGY AND FISHERIES
- Application of machine vision systems in aquaculture with emphasis on fish: state-of-the-art and key issues
- (2016) Mohammadmehdi Saberioon et al. Reviews in Aquaculture
- 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
- Herbivory and seasonal changes in diet of a highly endemic cyprinodontid fish (Aphanius farsicus)
- (2015) Carles Alcaraz et al. ENVIRONMENTAL BIOLOGY OF FISHES
- Transfer learning using computational intelligence: A survey
- (2015) Jie Lu et al. KNOWLEDGE-BASED SYSTEMS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Measuring feeding activity of fish in RAS using computer vision
- (2014) Ziyi Liu et al. AQUACULTURAL ENGINEERING
- idTracker: tracking individuals in a group by automatic identification of unmarked animals
- (2014) Alfonso Pérez-Escudero et al. NATURE METHODS
- Toward Scalable Systems for Big Data Analytics: A Technology Tutorial
- (2014) Han Hu et al. IEEE Access
- A hybrid WA–CPSO-LSSVR model for dissolved oxygen content prediction in crab culture
- (2013) Shuangyin Liu et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Fish species classification by color, texture and multi-class support vector machine using computer vision
- (2012) Jing Hu et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- The use of computer vision technologies in aquaculture – A review
- (2012) Boaz Zion COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Can marine fisheries and aquaculture meet fish demand from a growing human population in a changing climate?
- (2012) Gorka Merino et al. GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
- A computer-vision system and methodology for the analysis of fish behavior
- (2011) Vassilis M. Papadakis et al. AQUACULTURAL ENGINEERING
- Three-dimensional reconstruction of the fast-start swimming kinematics of densely schooling fish
- (2011) S. Butail et al. Journal of the Royal Society Interface
- The behavior of cod (Gadus morhua) in an offshore aquaculture net pen
- (2010) Chris Rillahan et al. AQUACULTURE
- A Survey on Transfer Learning
- (2009) Sinno Jialin Pan et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes
- (2008) S. Mahesh et al. BIOSYSTEMS ENGINEERING
- A survey of methods for image annotation
- (2008) Allan Hanbury JOURNAL OF VISUAL LANGUAGES AND COMPUTING
- Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
- (2008) Nicolas Le Roux et al. NEURAL COMPUTATION
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationPublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More