The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...
WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Looking back at 2025, it’s obviously, on a daily basis, why the broadcast networks are dismissed by most Americans as a source of daily advertising for one side of the political debate. This tilt has ...
Efficient Channel Attention-Gated Graph Transformer for Aero-Engine Remaining Useful Life Prediction
The rapid technological progress in recent years has driven industrial systems toward increased automation, intelligence, and precision. Large-scale mechanical systems are widely employed in critical ...
Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
Graph neural networks in Alzheimer's disease diagnosis: a review of unimodal and multimodal advances
Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...
Abstract: Deep learning (DL) has been widely applied in wireless communications to address diverse challenges, such as beam management, positioning, and channel state information (CSI) feedback.
A comprehensive PyTorch-based system for predicting cryptocurrency prices using a state-of-the-art Spatial-Temporal Graph Neural Network (ST-GNN) model. This advanced implementation integrates ...
Abstract: In recent years, superpixel-based graph convolutional networks (GCNs) have drawn increasing attention within the hyperspectral image (HSI) classification community. Due to the ...
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