Abstract
Image identification has been transformed by artificial intelligence (AI) and machine learning (ML), which are essential to marine technology. Using Convolutional Neural Networks (CNNs) for feature extraction, preprocessing, and data collecting, image recognition allows machines to recognize and categorize fish species. Fish species identification, size and weight estimate, and ecosystem monitoring are important applications that support the preservation of marine biodiversity and sustainable fisheries. High accuracy, scalability, and real- time analysis is provided by the technology, which lowers human error and enhances decision-making. However, issues including fish overcrowding, biofouling, and water turbidity may disrupt system function. Despite these drawbacks, developments in AI-powered picture identification keep improving environmental sustainability, fishery management, and marine research. This study shows how image recognition is becoming more and more capable of improving marine technology and encouraging responsible resource management
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Mohd Affandi, Nor Aina Afrina 2024672296@student.uitm.edu.my Uzair, Nur Atiqah 2024234546@student.uitm.edu.my Che Alias, Nurul Alia 2024406708@student.uitm.edu.my Othman, Jamal jamalothman@uitm.edu.my |
Contributors: | Contribution Name Email / ID Num. Chief Editor Othman, Jamal UNSPECIFIED |
Subjects: | L Education > LG Individual institutions > Asia > Malaysia > Universiti Teknologi MARA > Pulau Pinang L Education > LG Individual institutions > Asia > Malaysia > Universiti Teknologi MARA |
Divisions: | Universiti Teknologi MARA, Pulau Pinang > Permatang Pauh Campus |
Journal or Publication Title: | Beyond Boundaries: The Multidimensional Horizons of E-Learning |
ISSN: | 9786299875550 |
Volume: | 9 |
Page Range: | pp. 156-164 |
Keywords: | Artificial Intelligence, Machine Learning, Image recognition |
Date: | March 2025 |
URI: | https://ir.uitm.edu.my/id/eprint/114614 |