This document describes a methodology conceived to create ground truth datasets that may be exploited in the implementation of object detection and classification algorithms tailored on the Nephrops norvegicus. In fact, supervised machine learning algorithms usually require considerable amounts of annotated data to carry out the training stage. The greater the size of the annotated dataset, the stronger the required effort from the annotators.

Guidelines for the annotation of Nephrops norvegicus UWTV videos

Papini O.;Cecapolli E.;Domenichetti F.;Martinelli M.;Pieri G.;Reggiannini M.;Zacchetti L.
2025

Abstract

This document describes a methodology conceived to create ground truth datasets that may be exploited in the implementation of object detection and classification algorithms tailored on the Nephrops norvegicus. In fact, supervised machine learning algorithms usually require considerable amounts of annotated data to carry out the training stage. The greater the size of the annotated dataset, the stronger the required effort from the annotators.
2025
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Istituto per le Risorse Biologiche e le Biotecnologie Marine - IRBIM - Sede Secondaria Ancona
UWTV
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Descrizione: Guidelines for the annotation of Nephrops norvegicus UWTV videos
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/547369
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