  The target of this paper is to recommend a way for Automated classification
of Fish species. A high accuracy fish classification is required for greater
understanding of fish behavior in Ichthyology and by marine biologists.
Maintaining a ledger of the number of fishes per species and marking the
endangered species in large and small water bodies is required by concerned
institutions. Majority of available methods focus on classification of fishes
outside of water because underwater classification poses challenges such as
background noises, distortion of images, the presence of other water bodies in
images, image quality and occlusion. This method uses a novel technique based
on Convolutional Neural Networks, Deep Learning and Image Processing to achieve
an accuracy of 96.29%. This method ensures considerably discrimination accuracy
improvements than the previously proposed methods.
