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 ...
Abstract: In recent years, hyperspectral image classification methods based on convolutional neural networks and Transformer architectures have achieved remarkable success. However, existing ...
Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
CNN’s Harry Enten breaks down the numbers. Republican signals support for Trump impeachment 17 college basketball players charged in point-shaving scheme: Indictment I asked 3 restaurant pros to name ...
Elon Musk’s Grok chatbot has limited some of its Imagine image generation features to paid X subscribers, days after international uproar over the AI tool responded to user requests by “digitally ...
Abstract: Street view (SV) images provide valuable supplementary data for characterizing the functional attributes of land use types, improving urban land use classification based on ...
Founder Adam Martin and another top executive took tens of thousands of dollars in personal loans from the group’s funds. The board is now reviewing the situation. F5 Project founder and CEO Adam ...
Abstract: In recent years, uncrewed aerial vehicle (UAV) technology has shown great potential for application in hyperspectral image (HSI) classification tasks due to its advantages of flexible ...
A futuristic AI symbol hovers effortlessly, adorned with a bright red and white Christmas hat, blending holiday cheer with cutting-edge technology. The minimalist background accentuates the playful ...
The fate of Warner Bros. Discovery is no longer a regulatory matter. It is a medieval tournament, in which the king invites rival bidders to compete for his approval. To acquire the media company, the ...
Abstract: Semi-supervised learning (SSL) has achieved remarkable progress in the field of medical image segmentation (MIS), but it still faces two main challenges. First, the consistency learning ...