A Survey of Deep Learning Techniques for Underwater Image Classification
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PROJ20052
Description
In recent years, there has been an enormous interest in using deep learning to classify underwater images to identify various objects like fishes, rubber, rope, plastic, cloth and metal. This classification is essential for measuring the water bodies’ health and quality and protecting the endangered species. Further, it has applications in oceanography, marine economy and defence, environment protection, and underwater exploration and human-robot collaborative tasks. The system is developed the deep learning algorithm such as convolutional neural network (CNN) for classifying the underwater images effectively. Deep learning models require a large amount of data for achieving high accuracy. Here, we can implement the white balance techniques for enhancing the underwater images. Finally, the experimental results shows that accuracy.
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