MSCFNet: A Lightweight Network With Multi-Scale Context Fusion for Real-Time Semantic Segmentation

In recent years, how to strike a good trade-off between accuracy, inference speed, and model size has become the core issue for real-time semantic segmentation applications, which plays a vital role in real-world scenarios such as autonomous driving systems and drones. In this study, we devise a nov...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 23; H. 12; S. 25489 - 25499
Hauptverfasser:	Gao, Guangwei, Xu, Guoan, Yu, Yi, Xie, Jin, Yang, Jian, Yue, Dong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Asymmetry Coders Context context fusion Convolution Datasets Ear Encoders-Decoders encoder–decoder architecture Feature extraction Image segmentation Lightweight lightweight network Modules Parameters Real time Real-time semantic segmentation Real-time systems Semantic segmentation Semantics Task analysis
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!