CapsNets algorithm

doi:10.1088/1742-6596/1544/1/012030

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	CapsNets algorithm
	Zhang, Ping; Wei, Ping; Han, SHuhuan
	2020-06-02
会议日期	March 20, 2020 - March 22, 2020
会议地点	Suzhou, China
关键词	Convolutional neural networks Deep learning Formal languages Intelligent computing Object detection Semantics Computer classification Detection rates Hostile environments Neural network structures Semantic segmentation
卷号	1544
期号	1
DOI	10.1088/1742-6596/1544/1/012030
英文摘要	Capsule networks (CapsNets) is a commonly used neural network structure, especially in computer vision research., which may have a significant impact on deep learning. Convolutional neural networks (CNNs) have reached superhuman level in various computer classification tasks such as classification, parsing, object detection, semantic segmentation, and instance segmentation. Traditional deep learning tends to deteriorate when the relevance of detection objects changes. For this kind of situation, this paper improves a new network, namely the capsule network(CapsNets), the network can achieve a higher detection rate in the hostile environment. © 2019 Published under licence by IOP Publishing Ltd.
会议录	Journal of Physics: Conference Series
会议录出版者	IOP Publishing Ltd
语种	英语
ISSN号	17426588
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/118174]
专题	兰州理工大学
作者单位	School of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu; 730050, China
推荐引用方式 GB/T 7714	Zhang, Ping,Wei, Ping,Han, SHuhuan. CapsNets algorithm[C]. 见:. Suzhou, China. March 20, 2020 - March 22, 2020.