FishSense: Underwater RGBD Imaging for Fish Measurement-Reference-Cited by-同舟云学术

FishSense: Underwater RGBD Imaging for Fish Measurement

Published:2021-09-20 Issue: Volume: Page:
ISSN:
Container-title:OCEANS 2021: San Diego – Porto
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Author:

Tueller Peter¹,Maddukuri Raghav¹,Paxson Patrick¹,Suresh Vivaswat¹,Ashok Arjun²,Bland Madison³,Wallace Ronan⁴,Guerrero Julia⁵,Semmens Brice⁶,Kastner Ryan¹

Affiliation:

1. University of California,Department of Computer Science and Engineering,San Diego, La Jolla,CA

2. Dougherty Valley High School,San Ramon,CA

3. The College of New Jersey,Department of Electrical and Computer Engineering,Ewing,NJ

4. Macalester College,Department of Mathematics, Statistics, and Computer Science,Saint Paul,MN

5. University of California,Department of Mechanical and Aerospace Engineering,San Diego, La Jolla,CA

6. Scripps Institute of Oceanography, University of California,San Diego, La Jolla,CA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9705657/9705658/09705929.pdf?arnumber=9705929

Reference19 articles.

1. Tracking fish abundance by underwater image recognition;marinivimal;Scientific Reports,2018

2. Estimating the number of fish caught in global fishing each year;mood;Fishcount ¡ En línea,2010

3. Structured Light Methods for Underwater Imaging: Light Stripe Scanning and Photometric Stereo

4. Automatic measurement of fish size using stereo vision

5. Fish Classification Based on Underwater Image Interpolation and Back-Propagation Neural Network

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1. Fish Detection and Classification Based on Improved ViT;2023 2nd International Conference on Automation, Robotics and Computer Engineering (ICARCE);2023-12-14

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