TempNet: Temporal Attention Towards the Detection of Animal Behaviour in Videos

Author:

McIntosh Declan1,Marques Tunai Porto1,Branzan Albu Alexandra1,Rountree Rodney2,De Leo Fabio3

Affiliation:

1. University of Victoria,Department of Electrical and Computer Engineering,Victoria

2. University of Victoria,Department of Biology,Victoria

3. Ocean Networks Canada,Victoria

Publisher

IEEE

Reference25 articles.

1. Automatic Fish Population Counting by Machine Vision and a Hybrid Deep Neural Network Model

2. Detecting, tracking and counting fish in low quality unconstrained underwater videos;spampinato;VISAPP (2),2008

3. The potential of video imagery from worldwide cabled observatory networks to provide information supporting fish-stock and biodiversity assessment

4. Towards an optimal design for ecosystem-level ocean observatories;rountree;Oceanography and Marine Biology,2019

5. Movement tracks for the automatic detection of fish behavior in videos;mcintosh,2020

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