Acoustic video cameras multi-species multi-cameras Validation Dataset (VD) for Deep Learning applications

This video dataset, called also VD (Validation Dataset), is designed to test/validate, on a real-world case, deep learning models to identify fish species in sonar camers video flux. It includes data from two different type of cameras (ARIS and DIDSON), two sites (Touques and Selune rivers in Norman...

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Bibliographic Details
Main Authors: Fernandez Garcia, Guglielmo, Martignac, Fraçois
Format: Article in Journal/Newspaper
Language:unknown
Published: Zenodo 2021
Subjects:
deep learning
ARIS
DIDSON
sonar camera
acoustic camera video
freshwater fish
Aris
Atlantic salmon
European eel
Online Access:https://dx.doi.org/10.5281/zenodo.5092010
https://zenodo.org/record/5092010
Description
Summary:This video dataset, called also VD (Validation Dataset), is designed to test/validate, on a real-world case, deep learning models to identify fish species in sonar camers video flux. It includes data from two different type of cameras (ARIS and DIDSON), two sites (Touques and Selune rivers in Normandy, France), 6 different fishes classes (Atlantic Salmon, European Eel, Sea Lamprey, Allis Shad, European Catfish and generic unidentified fish). This dataset is composed by around 40h of videos, to test the efficiency of the models in the frame of ecological studies and to assess their real-applicability on monitoring sites data. Two sheets are given as the ground truth in which all fish passages (for fish sizes larger than 20 cm) are annotated. No bounding boxes are given.

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