Nowadays the most crucial aspect in Fisheries is the classification and localization of Fish. Due to Segmentation problems, noise and changes in the environmental conditions, it is difficult to classify the images with good accuracy. However, the object recognition with greater accuracy is in great demand. So, in order to solve this problem, the Convolutional Neural Network is used which helps to classify and localize the images with better accuracy. Fish classification is made by training the dataset and the level of accuracy has been improved by using different activation functions. Several comparisons have been made and finally a better method has been identified, thereby the accuracy is improved. Localization helps to generate Region proposals and class labels successfully. Finally, image classification and localization has been made with greater accuracy.
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Recognition Of Fish Categories Using Deep Learning Technique
Semantic Scholar · Computer Science · 2019
Abstract
Nowadays the most crucial aspect in Fisheries is the classification and localization of Fish. Due to Segmentation problems, noise and changes in the environmental conditions, it is difficult to classify the images with good accuracy. However, the object recognition with greater accuracy is in great demand. So, in order to solve this problem, the Convolutional Neural Network is used which helps to classify and localize the images with better accuracy. Fish classification is made by training the dataset and the level of accuracy has been improved by using different activation functions. Several comparisons have been made and finally a better method has been identified, thereby the accuracy is improved. Localization helps to generate Region proposals and class labels successfully. Finally, image classification and localization has been made with greater accuracy.