… We propose a deep neural fish classification system to automatically label fish using a …
environments robust solution for fish classification based on deep learning. The query images …

… This work aims to propose a fish classification system that works in natural underwater …
detect fishes with medicinal or nutritional importance. In this study, we use a hybrid deep learning …

… fish image analysis, to the best of our knowledge, no comprehensive survey and overview of
deep learning with a specific focus on fish classification … modern deep learning approaches …

… classification of Fish species. A high accuracy fish classification is required for greater
understanding of fish … Maintaining a ledger of the number of fishes per species and marking the …

… This paper focuses on applications of DL in aquaculture, including live fish identification,
species classification, behavioural analysis, feeding decisions, size or biomass estimation, and …

… fish classification. The RGB frame is also passed to YOLO classifier for fish localization and
classification. … For YOLO, we have utilised Tensor Flow deep learning libraries 3 while GMM …

… In this paper, we propose a two-step deep learning approach for the detection and classification
of temperate fishes without pre-filtering. The first step is to detect each single fish in an …

… for the task of fish classification using combination of fish-dependent features identified by …
suitable for fish recognition in underwater environments as the deep learning CNN technique …

… the accuracy of the classification of certain object [1,2]. Such is the case with the fish species
classification using image processing . Fish classification is an important process in many …

… The dataset used for this research work is taken from the QUT fish dataset [26]. It was used
to make a comparison among the deep learning structures. This dataset was used for the very …