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Infrared Images Augmentation Based on Images Generation with Generative Adversarial Networks
Chen FJ(陈佛计)1,2,3; Zhu F(朱枫)1,2,3; Wu QX(吴清潇)1,2,3; Hao YM(郝颖明)1,2,3; Cui YG(崔芸阁)1,2,3; Wang ED(王恩德)1,2,3
Department光电信息技术研究室
Conference Name2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Conference DateOctober 17-19, 2019
Conference PlaceBeijing, China
Author of SourceBeijing HIWING Scientific and Technological Information Institute ; Beijing Institute of Technology ; Chinese Institute of Command and Control, Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory ; Editorial Office of Unmanned Systems Technology ; et al. ; IEEE Beijing Section
Source PublicationProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
PublisherIEEE
Publication PlaceNew York
2019
Pages62-66
Indexed ByEI
EI Accession number20201008260694
Contribution Rank1
ISBN978-1-7281-3792-6
KeywordInfrared image generation Dataset augmentation generative adversarial networks
AbstractThe challenge brought by small data sets is a common problem in many computer visual tasks. The method of images generation with generative adversarial networks is investigated as a solution to extend small infrared datasets in this paper. In such a solution, the generation of infrared images is realized by generative adversarial networks by which RGB images can be translated to infrared images. The images generated by the generator of generative adversarial networks are of high quality, excluding some cases that the scene include rivers. Experiment results suggest that such an approach is effective in images generation for infrared dataset augmentation.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/26404
Collection光电信息技术研究室
Corresponding AuthorChen FJ(陈佛计)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences
3.University of Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Chen FJ,Zhu F,Wu QX,et al. Infrared Images Augmentation Based on Images Generation with Generative Adversarial Networks[C]//Beijing HIWING Scientific and Technological Information Institute, Beijing Institute of Technology, Chinese Institute of Command and Control, Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory, Editorial Office of Unmanned Systems Technology, et al., IEEE Beijing Section. New York:IEEE,2019:62-66.
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