ZMNet: feature fusion and semantic boundary supervision for real-time semantic segmentation

Ya Li; Ziming Li; Huiwang Liu; Qing‐Wen Wang

doi:10.1007/s00371-024-03448-6

ScienceGate Book Chapters

JOURNAL ARTICLE

ZMNet: feature fusion and semantic boundary supervision for real-time semantic segmentation

Ya Li Ziming Li Huiwang Liu Qing‐Wen Wang

Year: 2024 Journal: The Visual Computer Vol: 41 (3)Pages: 1543-1554 Publisher: Springer Science+Business Media

DOI: 10.1007/s00371-024-03448-6

Get Full-Text PDF Get Analytical Report

Keywords:

Feature (linguistics) Segmentation Computer science Fusion Semantic feature Boundary (topology) Artificial intelligence Natural language processing Pattern recognition (psychology) Mathematics Linguistics

Metrics

Cited By

4.24

FWCI (Field Weighted Citation Impact)

Refs

0.90

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

ZMNet: feature fusion and semantic boundary supervision for real-time semantic segmentation

Metrics

Citation History

Topics

Related Documents

Feature Reuse and Fusion for Real-Time Semantic Segmentation

Real-time Semantic Segmentation Method Based on Improved Feature Fusion

Real-Time Semantic Segmentation Algorithm Based on Feature Fusion Technology

Lightweight and efficient feature fusion real-time semantic segmentation network

CFFNet: Cross-scale Feature Fusion Network for Real-Time Semantic Segmentation