Novel Technique in Content Based Image Retrieval using Classification by Deep Learning in Artificial Intelligence
Keywords:
Content-based image retrieval, classification, DL, noise removal, ranking matrix, distance calculationAbstract
A popular technique for retrieving images from sizable and unlabeled image collections is content-based image retrieval (CBIR). One of the subcategories of the soft computing phenomenon known as "deep learning" allows for the retrieval of data from millions of separated images. This research propose novel technique in comprehensive description for content based image retrieval by classification utilizing DL techniques. Here input image has been collected and processed for noise removal. The processed image has been extracted and classified using FFCNN. Based on extracted features by calculating the similarity index of the images based on ranking matrix and distance calculation the image has been retrieved. The experimental analysis has been carried out in terms of accuracy, precision, recall, RMSE. the proposed technique attained accuracy of 95%, precision of 79%, recall of 68% and RMSE of 61%.
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Copyright (c) 2022 Nilanjana Saha , P. Thiruvannamalai Sivasankar , Rahama Salman , Badria Sulaiman Alfurhood , Aishwary Awasthi , Sukhwant Singh Bindra
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