SED-RCNN-BE: A SE-Dual channel RCNN network optimized binocular estimation model for automatic size estimation of free swimming fish in aquaculture-Reference-Cited by-同舟云学术

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SED-RCNN-BE: A SE-Dual channel RCNN network optimized binocular estimation model for automatic size estimation of free swimming fish in aquaculture

Published:2024-12 Issue: Volume:255 Page:124519
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Yu Huihui,Song Hexiang,Xu Ling^ORCID,Li Daoliang^ORCID,Chen Yingyi^ORCID

Funder

China Agricultural University

Beijing Forestry University

Publisher

Elsevier BV

Reference42 articles.

1. Method for measuring length of free-swimming farmed fry by 3D monitoring;Abe;Sensors and Materials,2020

2. An automated vision system for measurement of zebrafish length using low-cost orthogonal web cameras;Al-Jubouri;Aquacultural Engineering,2017

3. Underwater fish body length estimation based on binocular image processing;Cheng;Information,2020

4. Extracting fish size using dual underwater cameras;Costa;Aquacultural Engineering,2006

5. An automatic recognition method for fish species and length using an underwater stereo vision system;Deng;Fishes,2022

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