Image dataset for benchmarking automated fish detection and classification algorithms.
Marco FrancescangeliSimone MariniEnoc MartínezJoaquin Del Del RioDaniel M TomaMarc NoguerasJacopo AguzziPublished in: Scientific data (2023)
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.
Keyphrases
- deep learning
- artificial intelligence
- high frequency
- machine learning
- image quality
- big data
- quality control
- transcranial magnetic stimulation
- climate change
- computed tomography
- oxidative stress
- electronic health record
- air pollution
- minimally invasive
- human health
- magnetic resonance imaging
- optical coherence tomography
- loop mediated isothermal amplification
- risk assessment
- label free
- data analysis
- single cell