Image dataset for benchmarking automated fish detection and classification algorithms.

Autor:	Francescangeli, Marco, Marini, Simone, Martínez, Enoc, Del Río, Joaquín, Toma, Daniel M., Nogueras, Marc, Aguzzi, Jacopo
Předmět:	CLASSIFICATION of fish IDENTIFICATION of fishes CHRONOBIOLOGY ARTIFICIAL intelligence TIME series analysis VIDEO monitors CLASSIFICATION algorithms
Zdroj:	Scientific Data; 1/3/2023, Vol. 10 Issue 1, p1-13, 13p
Abstrakt:	Multiparametric video-cabled marine observatories are becoming strategic to monitor remotely and in real-time the marine ecosystem. Those platforms can achieve continuous, high-frequency and long-lasting image data sets that require automation in order to extract biological time series. The OBSEA, located at 4 km from Vilanova i la Geltrú at 20 m depth, was used to produce coastal fish time series continuously over the 24-h during 2013–2014. The image content of the photos was extracted via tagging, resulting in 69917 fish tags of 30 taxa identified. We also provided a meteorological and oceanographic dataset filtered by a quality control procedure to define real-world conditions affecting image quality. The tagged fish dataset can be of great importance to develop Artificial Intelligence routines for the automated identification and classification of fishes in extensive time-lapse image sets. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
Externí odkaz:	Zobrazit plný text záznamu Full text from SpringerLink