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 ...
Abstract: With the gradual maturity of deep learning technology and its extensive application in the field of remote sensing, hyperspectral image (HSI) classification technology has made tremendous ...
Abstract: Knowledge distillation (KD) has recently demonstrated remarkable potential in developing lightweight convolutional neural networks for remote sensing image (RSI) scene classification tasks.
Abstract: Fine-grained flower image classification (FGFIC) is challenging due to high similarities among species and variations within species, especially with limited training data. Existing genetic ...
Abstract: Deep learning models have shown impressive performance across a range of computer vision tasks. However, their lack of transparency limits their adoption in tasks where a clear understanding ...
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 ...
Image Analysis Group and Ferring validate AI imaging biomarkers with FCI and Dexeus to optimize conception timing and personalize fertility care. Image-centric AI collaboration between Image Analysis ...
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 ...
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: Vision transformers (ViTs) and convolutional neural networks (CNNs) have demonstrated remarkable performance in classifying complicated hyperspectral images (HSIs). However, these models ...
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