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SECOND is a well-annotated benchmark for SCD. It collects bitemporal aerial images covering Hangzhou, Chengdu, Shanghai and other cities. The number of images totals 4662 pairs, of which 2968 pairs are used for training and 1694 pairs are used for testing. Each image has a size of 512 × 512 pixels with a spatial resolution from 0.5m to 3m. SENCOND provides unchanged masks and land cover masks in changed areas. It focuses on 6 common land cover classes, i.e., non-vegetated ground surface, tree, low vegetation, water, buildings and playgrounds.
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Osteoarthritis (OA) is a prevalent degenerative joint disease,particularly affecting the knees. Early and accurate detection of OA and its severity, often graded using the Kellgren-Lawrence (KL) scale, is crucial for timely intervention and management. This study explores the application of deep learning techniques to automatically detect OA and assign KL grades from knee X-ray images. We propose a novel deep learning architecture that effectively extracts relevant features from X-ray images and classifies them into different KL grades.
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