Abstract: In this article, a multimodal deep architecture for classification of light detection and ranging (LiDAR) and hyperspectral image (HSI) is proposed, acquiring the knowledge of both ...

Abstract: Breast cancer is the most frequent type of cancer largely experienced by women currently, although it could happen to men also. It appears when abnormal breast tissue cells grow rapidly and ...

Abstract: In recent years, graph convolutional networks (GCNs) have been introduced for hyperspectral image (HSI) classification due to their ability to effectively process the inherent graph ...

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: To obtain light ensemble model through clearly explained effective ensemble member selection and finding data representation in various valuable forms are major challenges in medical image ...

Abstract: Vision transformers (ViTs) and convolutional neural networks (CNNs) have demonstrated remarkable performance in classifying complicated hyperspectral images (HSIs). However, these models ...

Abstract: Traditional brain tumor diagnosis and classification are time-consuming and heavily reliant on radiologist expertise. The ever-growing patient population generates vast data, rendering ...

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Physicists are exploring a quantum-mechanical approach to making smaller radio wave detectors. Physicists have created a new type of radar that could help improve underground imaging, using a cloud of ...