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...

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Vydané v:	IEEE transactions on intelligent transportation systems Ročník 23; číslo 12; s. 25489 - 25499
Hlavní autori:	Gao, Guangwei, Xu, Guoan, Yu, Yi, Xie, Jin, Yang, Jian, Yue, Dong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.12.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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