Results 41 to 50 of about 1,221,513 (328)
Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks [PDF]
Remote Sensing of Environment, 2023 Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on individual urban environments (e.g., single cities or regions).
D. Hong +9 more
semanticscholar +1 more source
IEEE Access, 2023 As a critical step in 3D scene understanding, semantic segmentation of point clouds has broad application scenarios, including intelligent driving, augmented reality, smart factories, etc.
Ansi Zhang +4 more
doaj +1 more source
Joint Learning of Intrinsic Images and Semantic Segmentation [PDF]
, 2018 Semantic segmentation of outdoor scenes is problematic when there are variations in imaging conditions. It is known that albedo (reflectance) is invariant to all kinds of illumination effects. Thus, using reflectance images for semantic segmentation task
A Garcia-Garcia +13 more
core +2 more sources
Scene-Aware Deep Networks for Semantic Segmentation of Images
IEEE Access, 2019 Scene classification and semantic segmentation are two important research directions in computer vision. They are widely used in the research of automatic driving and human–computer interaction.
Zhike Yi +5 more
doaj +1 more source
Attention-Based Joint Semantic-Instance Segmentation of 3D Point Clouds
Advances in Electrical and Computer Engineering, 2022 In this paper, we propose an attention-based instance and semantic segmentation joint approach, termed ABJNet, for addressing the instance and semantic segmentation of 3D point clouds simultaneously.
HAO, W. +4 more
doaj +1 more source
Image Semantic Segmentation Method with Hierarchical Feature Fusion
Jisuanji kexue yu tansuo, 2021 When image feature information extraction is performed by using convolutional networks in the image semantic segmentation, the feature information between levels is not used effectively, resulting in image segmentation accuracy impaired.
ZHAO Xiaoqiang, XU Huiping
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Survey of Point Cloud Semantic Segmentation Based on Deep Learning
Jisuanji kexue yu tansuo, 2021 In recent years, the popularity of depth sensors and 3D laserscanners has led to a rapid development of 3D point clouds processing methods. Semantic segmentation of point cloud, as a key step in understanding 3D scenes, has attracted extensive attention ...
JING Zhuangwei, GUAN Haiyan, ZANG Yufu, NI Huan, LI Dilong, YU Yongtao
doaj +1 more source
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds [PDF]
Computer Vision and Pattern Recognition, 2019 We study the problem of efficient semantic segmentation for large-scale 3D point clouds. By relying on expensive sampling techniques or computationally heavy pre/post-processing steps, most existing approaches are only able to be trained and operate over
Qingyong Hu +7 more
semanticscholar +1 more source
Convolutional neural network-based automated segmentation and labeling of the lumbar spine X-ray
Journal of Craniovertebral Junction and Spine, 2021 Purpose: This study investigated the segmentation metrics of different segmentation networks trained on 730 manually annotated lateral lumbar spine X-rays to test the generalization ability and robustness which are the basis of clinical decision support ...
Sandor Konya +5 more
doaj +1 more source
FDA: Fourier Domain Adaptation for Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2020 We describe a simple method for unsupervised domain adaptation, whereby the discrepancy between the source and target distributions is reduced by swapping the low-frequency spectrum of one with the other. We illustrate the method in semantic segmentation,
Yanchao Yang, Stefano Soatto
semanticscholar +1 more source