Optical Fish Trajectory Measurement in Fishways through Computer Vision and Artificial Neural Networks-Reference-Cited by-同舟云学术

Optical Fish Trajectory Measurement in Fishways through Computer Vision and Artificial Neural Networks

Published:2011-07 Issue:4 Volume:25 Page:291-301
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Rodriguez Álvaro¹²³²¹,Bermúdez María¹²³²¹,Rabuñal Juan R.¹²³²¹,Puertas Jerónimo¹²³²¹,Dorado Julián¹²³²¹,Pena Luís¹²³²¹,Balairón Luis¹²³²¹

Affiliation:

1. Faculty of Informatics, Dept. of Information and Communications Technologies, Univ. of A Coruña, Campus Elviña s/n 15071, A Coruña, Spain.

2. Dept. of Hydraulic Engineering, ETSEC, Univ. of A Coruña, Campus Elviña s/n 15071, A Coruña, Spain.

3. Center of Technological Innovation in Construction and Civil Engineering (CITEEC), Univ. of A Coruña, Campus Elviña s/n 15071, A Coruña, Spain (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000092

Reference34 articles.

1. Two-stage neural network for volume segmentation of medical images

2. Photographic and acoustic tracking observations of the behaviour of the grenadier Coryphaenoides (Nematonurus) armatus the eel Synaphobranchus bathybius, and other abyssal demersal fish in the North Atlantic Ocean

3. Fish functional design and swimming performance

4. A passive integrated transponder (PIT) tag system for monitoring fishways

5. Application of Several Depth-Averaged Turbulence Models to Simulate Flow in Vertical Slot Fishways

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