A Feature Learning and Object Recognition Framework for Underwater Fish Images
Product Description
A Feature Learning and Object Recognition
Framework for Underwater Fish Images
Abstract— Live fish recognition is one of the most crucial elements of fisheries survey applications where the vast amount of data is rapidly acquired. Different from general scenarios, challenges to underwater image recognition are posted by poor image quality, uncontrolled objects and environment, and difficulty in acquiring representative samples. In addition, most existing feature extraction techniques are hindered from automation
due to involving human supervision. Toward this end, we propose an underwater fish recognition framework that
consists of a fully unsupervised feature learning technique and an error-resilient classifier. Object parts are initialized based on saliency and relaxation labeling to match object parts correctly. < final year projects >
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