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Technology of Graphic & Image
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3842-3845,3852

Proposal adaptive detection method for small sample reticular structures

Mou Leia,b
Chen Lia,b
a. School of Computer Science & Technology, b. Hubei Province Key Laboratory of Intelligent Information Processing & Real-time Industrial System, Wuhan University of Science & Technology, Wuhan 430065, China

Abstract

The detection performance of the object detection model requiring a large amount of training data is greatly reduced in the reticular structures detection task with a small amount of labeled data. The detection model which based on region proposals will spend longer time with larger outputs during predicting. And the number of reticular structures are different in different images. It will result in extra time consumption in object detection if the number of proposals is fixed in different images. In view of this problem, this paper proposed a proposal adaptive detection method for small sample reticular structures by analyzing the density of the reticular structures in the training samples and according to the characteristic distribution of the reticular structures in the images. This method obtained a large number of training samples by the method of binary-value labeled map marking, and selected a reasonable number of proposals by the proposal adaptive method. Compared with the unimproved model, the detection speed of proposed method is accelerated without loss of accuracy, especially in the data with few objects.

Foundation Support

国家自然科学基金资助项目(61773297,61375017)
智能信息处理与实时工业系统湖北省重点实验室开放基金资助项目(2016znss01A)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0427
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 12
Section: Technology of Graphic & Image
Pages: 3842-3845,3852
Serial Number: 1001-3695(2019)12-071-3842-04

Publish History

[2019-12-05] Printed Article

Cite This Article

牟磊, 陈黎. 面向少样本网状结构体的候选区域自适应检测方法 [J]. 计算机应用研究, 2019, 36 (12): 3842-3845,3852. (Mou Lei, Chen Li. Proposal adaptive detection method for small sample reticular structures [J]. Application Research of Computers, 2019, 36 (12): 3842-3845,3852. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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