ELMF-Net: Semantic Segmentation of Large-Scale Point Clouds via Efficient Local Feature Learner and Multiscale Fusion

Maomao Sun; Ting Rui; Dong Wang; Chengsong Yang; Nan Zheng

doi:10.1109/jsen.2025.3534319

ScienceGate Book Chapters

JOURNAL ARTICLE

ELMF-Net: Semantic Segmentation of Large-Scale Point Clouds via Efficient Local Feature Learner and Multiscale Fusion

Maomao Sun Ting Rui Dong Wang Chengsong Yang Nan Zheng

Year: 2025 Journal: IEEE Sensors Journal Vol: 25 (7)Pages: 11392-11404 Publisher: IEEE Sensors Council

DOI: 10.1109/jsen.2025.3534319

Get Full-Text PDF Get Analytical Report

Keywords:

Scale (ratio) Point cloud Segmentation Computer science Feature (linguistics) Artificial intelligence Fusion Point (geometry) Pattern recognition (psychology) Net (polyhedron) Computer vision Mathematics Geography Cartography

Metrics

Cited By

9.55

FWCI (Field Weighted Citation Impact)

Refs

0.90

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Image Processing and 3D Reconstruction

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Remote Sensing and LiDAR Applications

Physical Sciences → Environmental Science → Environmental Engineering

3D Surveying and Cultural Heritage

Physical Sciences → Earth and Planetary Sciences → Geology

ELMF-Net: Semantic Segmentation of Large-Scale Point Clouds via Efficient Local Feature Learner and Multiscale Fusion

Metrics

Citation History

Topics

Related Documents

RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds

MSFD-Net: A Multiscale Spatial Feature Descriptor Network for Semantic Segmentation of Large-Scale Bridge Point Clouds

Feature Graph Convolution Network With Attentive Fusion for Large-Scale Point Clouds Semantic Segmentation

Edge-Convolution Point Net for Semantic Segmentation of Large-Scale Point Clouds

EEP-Net: Enhancing Local Neighborhood Features and Efficient Semantic Segmentation of Scale Point Clouds