Results 1 to 10 of about 368,354 (280)

Back to geometry: Efficient indoor space segmentation from point clouds by 2D–3D geometry constrains

International Journal of Applied Earth Observations and Geoinformation
This paper addresses the challenge of indoor space segmentation from 3D point clouds, which is essential for understanding interior layouts, reconstructing 3D structures, and developing indoor navigation maps.
Shengjun Tang, Junjie Huang, Benhe Cai, Han Du, Baoding Zhou, Zhigang Zhao, You Li, Weixi Wang, Renzhong Guo   +8 more
doaj   +1 more source

TriM-SOD: A Multi-Modal, Multi-Task, and Multi-Scale Spacecraft Optical Dataset

Space: Science & Technology
The acquisition and application of spacecraft optical data is an important part of space-based situational awareness (SSA). Spacecraft optical data processing techniques can assist in tasks such as on-orbit operation, space debris removal, and deep space
Tianyu Zhu, Hesong Li, Ying Fu
doaj   +1 more source

Dual-Consistency Input-Space Domain Adaptation for Remote Sensing Image Semantic Segmentation via SSC-CycleGAN

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In remote sensing image semantic segmentation, unsupervised domain adaptation (UDA) addresses two key challenges: scarce labeled data and poor cross-domain generalization. By narrowing domain shift between labeled source and unlabeled target domains, UDA
Longbao Wang, Yiding Ma, Meng Ding, Yinqi Luan, Shun Luo, Xiaoyang Meng, Yueyang Mao, Hongmin Gao   +7 more
doaj   +1 more source

Direction-guided grouping for point cloud semantic segmentation in coal mine roadways

Meitan kexue jishu
Point cloud semantic segmentation in coal mine roadways is a critical technology for scene understanding in underground coal mine environments. However, the coexistence of multi-scale objects and imbalanced class samples in mine point clouds lead to poor
Jian CHENG, Shuchen ZHANG, Heping LI, Ning AN, Hailong ZHAO, Haixin XIU   +5 more
doaj   +1 more source

Scale Space Approximation in Convolutional Neural Networks for Retinal Vessel Segmentation

, 2018
10 pages, 7 ...
Noh, Kyoung Jin, Park, Sang Jun, Lee, Soochahn   +2 more
openaire   +2 more sources

Semantic Segmentation Network Based on Adaptive Attention and Deep Fusion Utilizing a Multi-Scale Dilated Convolutional Pyramid

Sensors
Deep learning has recently made significant progress in semantic segmentation. However, the current methods face critical challenges. The segmentation process often lacks sufficient contextual information and attention mechanisms, low-level features lack
Shan Zhao, Zihao Wang, Zhanqiang Huo, Fukai Zhang   +3 more
doaj   +1 more source

CUS3D: A New Comprehensive Urban-Scale Semantic-Segmentation 3D Benchmark Dataset

Remote Sensing
With the continuous advancement of the construction of smart cities, the availability of large-scale and semantically enriched datasets is essential for enhancing the machine’s ability to understand urban scenes.
Lin Gao, Yu Liu, Xi Chen, Yuxiang Liu, Shen Yan, Maojun Zhang   +5 more
doaj   +1 more source

Lumbar and pelvic CT image segmentation based on cross-scale feature fusion and linear self-attention mechanism

Scientific Reports
The lumbar spine and pelvis are critical stress-bearing structures of the human body, and their rapid and accurate segmentation plays a vital role in clinical diagnosis and intervention.
Chaofan Li, Liping Chen, Qiong Liu, Jinnan Teng   +3 more
doaj   +1 more source

A cognitive deep learning approach for medical image processing

Scientific Reports
In ophthalmic diagnostics, achieving precise segmentation of retinal blood vessels is a critical yet challenging task, primarily due to the complex nature of retinal images.
Hussam N. Fakhouri, Sadi Alawadi, Feras M. Awaysheh, Fahed Alkhabbas, Jamal Zraqou   +4 more
doaj   +1 more source

SAGNet: Small-Target Attention Guided Network for Urban Remote Sensing Image Real-Time Segmentation

IEEE Access
High-precision real-time segmentation of urban remote sensing (URS) images is crucial for emergency response such as urban flood warning and fire spread monitoring.
Shasha Ren, Xiaodong Zhang
doaj   +1 more source