As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...
Overview of VeloxSeg. VeloxSeg employs an encoder-decoder architecture with Paired Window Attention (PWA) and Johnson-Lindenstrauss lemma-guided convolution (JLC) on the left, using 1x1 convolution as ...
Abstract: Local spectral features and global spatial context are essential for hyperspectral image (HSI) classification. However, existing methods based on convolutional neural networks (CNNs), graph ...
Objective: Melasma is a common acquired facial hyperpigmentation disorder characterized by symmetrical brown patches, often occurring in the zygomatic region, forehead, and upper lip. Its blurred ...
Abstract: Weakly-supervised point cloud semantic segmentation (WS-PCS) has attracted increasing attention due to the challenge of sparse annotations. A central problem is how to effectively extract ...
Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
AI for Science Institute (CUAISci), Cornell University, Ithaca, New York 14853, United States Systems Engineering, College of Engineering, Cornell University, Ithaca, New York 14853, United States AI ...
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