IEEE

BGC-Net: Bilateral Graph Convolutional Network for Weakly-supervised Semantic Segmentation of Large-scale Point Clouds

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 ...
Morningstar

WiMi Lays Out Scalable Quantum Convolutional Neural Network to Enhance Image Classification Accuracy and Efficiency

BEIJING, Sept. 15, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that ...
C&EN

DCGCN: Dual-Channel Graph Convolutional Network-Based Drug–Target Interaction Prediction Method with 3D Molecular Structure

College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin ...
Forbes

Security Graphs Explained: An Innovative Approach To Network Security

Imagine standing atop a mountain, gazing at the vast landscape below, trying to make sense of the world around you. For centuries, explorers relied on such vantage points to map their surroundings.
ascopubs.org

Performance analysis of artificial intelligence–driven convolutional neural network architectures for liver tumor segmentation.

Comparative efficacy and safety of donafenib versus bevacizumab in combination with immune checkpoint inhibitors and interventional therapy for advanced hepatocellular carcinoma: A retrospective ...
Frontiers

Multi-Conv attention network for skin lesion image segmentation

1 International College, Chongqing University of Posts and Telecommunications, Chongqing, China 2 Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States To ...
Frontiers

A 3D Fully Convolutional Neural Network With Top-Down Attention-Guided Refinement for Accurate and Robust Automatic Segmentation of Amygdala and Its Subnuclei

Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most ...