Abstract: Hyperspectral image (HSI) classification demands models that can jointly capture long-range spatial relations and high-dimensional spectral structures while remaining scalable to large ...
Abstract: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical importance of early and accurate detection in improving patient outcomes and treatment ...
Abstract: Magnetic resonance imaging (MRI) is an important tool for brain cancer diagnosis and classification. Combined with modern convolutional neural network (CNN) technology, it can effectively ...
Abstract: Accurate classification of otoscopic ear images is crucial for early diagnosis of ear pathologies such as Chronic Otitis Media, Earwax Plug, and Myringosclerosis. In this study, we propose a ...
Video and images showing an armed, masked individual outside the Tucson, Arizona, home of Nancy Guthrie have given new life to the search for the 84-year-old – and may offer investigators important ...
Abstract: Hyperspectral image classification is a fundamental task in remote sensing with broad applications in precision agriculture, environmental monitoring, and related fields. However, existing ...
A flamboyance of flamingos dazzling against a backdrop of power lines, a crafty crab hitching a ride on a jellyfish and a young sloth safe in his mother’s embrace are among the shortlisted images for ...
First it was the Oval Office, then the East Wing, and now Donald Trump wants to remodel the Kennedy Center ... A five-year-old boy detained by ICE is now back home as Congress fights over reforms to ...
Abstract: In hyperspectral image (HSI) classification, Transformer and CNN are widely used because they complement each other in extracting features. Nevertheless, existing Transformer-based methods ...
Hyperspectral image (HSI) classification aims at categorizing each pixel in an HSI, facilitating precise identification and differentiation of various land cover types. In recent years, graph neural ...
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