A compression pipeline for one-stage object detection model

Deep neural networks (DNNs) have strong fitting ability on a variety of computer vision tasks, but they also require intensive computing power and large storage space, which are not always available in portable smart devices. Although a lot of studies have contributed to the compression of image cla...

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Veröffentlicht in:	Journal of real-time image processing Jg. 18; H. 6; S. 1949 - 1962
Hauptverfasser:	Li, Zhishan, Sun, Yiran, Tian, Guanzhong, Xie, Lei, Liu, Yong, Su, Hongye, He, Yifan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial neural networks Classification Computer Graphics Computer Science Computer vision Distillation Floating point arithmetic Image classification Image compression Image Processing and Computer Vision Integers Knowledge Knowledge management Learning Methods Multimedia Information Systems Neural networks Object recognition Original Research Paper Pattern Recognition Portable equipment Signal,Image and Speech Processing Training Model compression pipeline Real-time Object detection
ISSN:	1861-8200, 1861-8219
Online-Zugang:	Volltext
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