Res2Net: A New Multi-Scale Backbone Architecture

Representing features at multiple scales is of great importance for numerous vision tasks. Recent advances in backbone convolutional neural networks (CNNs) continually demonstrate stronger multi-scale representation ability, leading to consistent performance gains on a wide range of applications. Ho...

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Vydané v:	IEEE transactions on pattern analysis and machine intelligence Ročník 43; číslo 2; s. 652 - 662
Hlavní autori:	Gao, Shang-Hua, Cheng, Ming-Ming, Zhao, Kai, Zhang, Xin-Yu, Yang, Ming-Hsuan, Torr, Philip
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.02.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Ablation Artificial neural networks Backbone Computer architecture Computer vision Convolution deep learning Feature extraction Kernel Multi-scale Object detection Object recognition Salience Semantics Source code Task analysis
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
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