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Integration of sonar and optical camera images using deep neural network for fish monitoring
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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U-Net: Convolutional Networks for Biomedical Image Segmentation
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Generative Adversarial Nets
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Fish sizing and monitoring using a stereo image analysis system applied to fish farming
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Extracting fish size using dual underwater cameras
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A computer vision system to analyse the swimming behaviour of farmed fish in commercial aquaculture facilities: A case study using cage-held Atlantic salmon
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Monitoring fish weight using pulse-echo waveform metrics
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Benthic fish behavior characterization with a mechanically scanned imaging sonar
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The use of computer vision technologies in aquaculture – A review
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Accuracy and precision of fish-count data from a “dual-frequency identification sonar” (DIDSON) imaging system
inferredcites →https://doi.org/10.1017/s0263574702004733openalex-snapshot
Computer vision and robotics techniques in fish farms
inferredcites →https://doi.org/10.1038/srep31810openalex-snapshot
A highly sensitive underwater video system for use in turbid aquaculture ponds
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Image-to-Image Translation with Conditional Adversarial Networks
inferredcites →https://doi.org/10.1109/eurcon.2003.1248032openalex-snapshot
Colour spaces: perceptual, historical and applicational background
inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot
Image quality assessment: from error visibility to structural similarity
inferredcites →https://doi.org/10.1109/ut.2002.1002424openalex-snapshot
Dual-Frequency Identification Sonar (DIDSON)
inferredcites →https://doi.org/10.1111/faf.12071openalex-snapshot
The use of acoustic cameras in shallow waters: new hydroacoustic tools for monitoring migratory fish population. A review of DIDSON technology
inferredcites →https://doi.org/10.1117/12.2020941openalex-snapshot
A review of techniques for the identification and measurement of fish in underwater stereo-video image sequences
inferredcites →https://doi.org/10.1142/s1793351x15400012openalex-snapshot
A Measurement Method for Speed Distribution of Collective Motion with Optical Flow and Its Applications to School of Fish
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1577/t09-173.1openalex-snapshot
Accuracy and Precision of Salmon Length Estimates Taken from DIDSON Sonar Images
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GAN（Generative Adversarial Nets）
inferredcites →https://doi.org/10.48550/arxiv.1506.05751openalex-snapshot
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
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DETECTING, TRACKING AND COUNTING FISH IN LOW QUALITY UNCONSTRAINED UNDERWATER VIDEOS
inferredcites →https://doi.org/10.5657/fas.2011.0218openalex-snapshot
Semiautomated Analysis of Data from an Imaging Sonar for Fish Counting, Sizing, and Tracking in a Post-Processing Application
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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