Semi-supervised semantic segmentation with confidence-driven consistency learning

Fangqing Sheng; Ye Zhu; Lei Jin; Jianjian Yin

doi:10.1016/j.eswa.2025.128965

ScienceGate Book Chapters

JOURNAL ARTICLE

Semi-supervised semantic segmentation with confidence-driven consistency learning

Fangqing Sheng Ye Zhu Lei Jin Jianjian Yin

Year: 2025 Journal: Expert Systems with Applications Vol: 296 Pages: 128965-128965 Publisher: Elsevier BV

DOI: 10.1016/j.eswa.2025.128965

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Artificial intelligence Consistency (knowledge bases) Segmentation Machine learning Semi-supervised learning Natural language processing Pattern recognition (psychology)

Metrics

Cited By

4.82

FWCI (Field Weighted Citation Impact)

Refs

0.94

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Machine Learning and Data Classification

Physical Sciences → Computer Science → Artificial Intelligence

Semi-supervised semantic segmentation with confidence-driven consistency learning

Metrics

Citation History

Topics

Related Documents

Semi-Supervised Semantic Segmentation With Multi-Constraint Consistency Learning

Progressive Learning With Cross-Window Consistency for Semi-Supervised Semantic Segmentation

Semi-supervised Medical Image Segmentation with Semantic Distance Distribution Consistency Learning

Revisiting Consistency for Semi-Supervised Semantic Segmentation

Uncertainty-Participation Context Consistency Learning for Semi-supervised Semantic Segmentation