Title: Fish Species Classification Using Deep Learning
Authors: Taha Mohamed Ali Al-Jaro , Mohammed Osama Abdelazez Esleem, Samy S. Abu-Nasser
Volume: 10
Issue: 2
Pages: 58-65
Publication Date: 2026/02/28
Abstract:
Fish represent one of the most diverse groups of vertebrates inhabiting aquatic environments, including freshwater and marine ecosystems. They play a crucial role in ecological balance and are considered an essential source of nutrition for humans. Due to the large number of fish species and their significant variation in physical characteristics, accurate identification and classification have become increasingly important in biological studies, fisheries management, and environmental conservation. This study focuses on the classification of different types of fish based on their morphological characteristics such as body shape, fin structure, size, and coloration. Visual data, including fish images, are utilized to highlight the distinguishing features among various species. The use of image-based analysis contributes to improving the understanding of fish diversity and supports effective species recognition. The outcomes of this study aim to enhance knowledge in marine biology and provide a foundation for future research in fish classification and aquatic resource management..