Abstract: Classifying high-resolution remote sensing images is an essential task for resource management, urban planning, and environmental monitoring; however, it is still difficult because of the ...
Abstract: Hyperspectral image (HSI) captured by uncrewed aerial vehicles (UAVs) is distinguished by superior spatial resolution and intricate spectral detail, with widespread applications in precise ...
Abstract: Deep learning models, especially hybrid models combining convolutional neural networks (CNN) and Transformer, introduce new ideas for hyperspectral image (HSI) classification. However, the ...
Abstract: State-space models (SSMs), particularly the Mamba model, have recently garnered significant attention in hyperspectral image (HSI) classification tasks due to their capability to model ...
Abstract: Hyperspectral image classification (HSIC) is a critical task in remote sensing. However, the performance of deep-learning-based HSIC methods degrades significantly when training data ...
Abstract: Anaemia is a condition marked by an insufficient number of healthy red blood cells, often initially indicated through visible conjunctival pallor. Conventional diagnostic approaches rely on ...
Abstract: Hyperspectral image (HSI) classification is a critical task in remote sensing. Recently, deep learning (DL) methods, particularly state space models (SSMs) like Mamba, have garnered ...
NASA released the very first images taken by astronauts aboard the Artemis II Orion capsule as they are making their way to the moon. The stunning pictures were taken by mission commander Reid Wiseman ...
Abstract: Short term solar irradiance is used for forecasting and the integration of systems that are photovoltaic into the modern power grids. Cloud formation movements and the density degrade the ...
Abstract: One of the key challenges in cross-domain few-shot hyperspectral image classification (HSIC) lies in effectively leveraging spectral-spatial features while alleviating semantic ...
Abstract: Accurate classification of brain tumors from magnetic resonance imaging (MRI) scans is essential for early diagnosis and reliable clinical decision-making. However, variations in tumor ...
Abstract: Various deep learning-based methods have greatly improved hyperspectral image (HSI) classification performance, but these models are sensitive to noisy training labels. Human annotation on ...
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