Graph convolutional networks demonstrate advantages such as low sample requirements and strong global information modeling capabilities in the semantic segmentation of synthetic aperture radar (SAR).

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 ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

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 ...

Department of Materials Science and Engineering, Indian Institute of Technology, Delhi-110016, India Department of Chemistry, Indian Institute of Technology, Delhi-110016, India ...

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

All resulting images and pre-trained models are available in the provided links. 11/26/2024 Code for real haze and haze4k are released. 07/22/2024 We release the code for dehazing (ITS/OTS), desnowing ...

Abstract: This paper proposes a hierarchical depthwise graph convolutional neural network (HDGCN) for point cloud semantic segmentation. The main chanllenge for learning on point clouds is to capture ...