AI-powered knowledge graph links heart images to genes and drug predictions

Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already ...
The American Journal of Managed Care

Convolutional Neural Network Improves MS Lesion Segmentation

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, making it more applicable in clinical settings. The algorithm outperformed ...
Frontiers

Multi-Scale graph wavelet convolutional network for hyperspectral image classification

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
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 ...
Oak Ridge National Lab

GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism...

Proceedings of The Eighth Annual Conference on Machine Learning and Systems Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their ...
IEEE

Segmentation of Hemorrhagic Stroke Using Graph Convolutional Network

Abstract: Stroke is a serious global public health problem, and several studies on tools to assist its diagnosis have been conducted, many of them involving image processing techniques and deep ...
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 ...