International Journal of Intelligent Machines and Robotics
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International Journal of Intelligent Machines and Robotics (1 paper in press)
Deep learning-based approach for recognition of local fish by Masum Shah Junayed, Afsana Ahsan Jeny, Md. Tarek Habib, Md. Sadekur Rahman Abstract: Bangladesh is a riverine country with thousands of rivers and ponds. Bangladesh, being a fish-loving nation, is considered one of the most suitable areas for fish culture. People of this generation in Bangladesh usually fail to recognise the local freshwater fish. Performing a classification of freshwater fish can help people recognise the local fish of Bangladesh. In this way, a vital part of the cultural heritage of Bangladesh can be retained. In this paper, a number of local freshwater fish are classified based on their characteristics. For this reason, we take a purpose for identifying fish. For our experiment, we have used total 6,000 images of ten local freshwater fish. We have used four convolutional neural network models, namely Inception-V3, MobileNet, ResNet50, and Xception for classifying the fish. We have obtained good accuracy, i.e., more than 95% with all four models, where MobileNet outperforms all other models by showing an accuracy of 98.41%. Keywords: artificial intelligence; convolutional neural networks; deep learning; local fish detection; transfer learning; computer vision; Bangladesh. DOI: 10.1504/IJIMR.2020.10030951