Usman Ahmad1, Muhammad Junaid Ali2, Faizan Ahmed Khan3, Arfat Ahmad Khan4, Arif Ur Rehman1, Malik Muhammad Ali Shahid5, Mohd Anul Haq6,*, Ilyas Khan7, Zamil S. Alzamil6, Ahmed Alhussen8
Computer Systems Science and Engineering, Vol.45, No.2, pp. 2125-2140, 2023, DOI:10.32604/csse.2023.031008
Abstract Building an automatic fish recognition and detection system for large-scale fish classes is helpful for marine researchers and marine scientists because there are large numbers of fish species. However, it is quite difficult to build such systems owing to the lack of data imbalance problems and large number of classes. To solve these issues, we propose a transfer learning-based technique in which we use Efficient-Net, which is pre-trained on ImageNet dataset and fine-tuned on QuT Fish Database, which is a large scale dataset. Furthermore, prior to the activation layer, we use Global Average Pooling (GAP) instead of dense layer with… More >
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