政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/129022

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113311/144292 (79%)
Visitors : 50923353 Online Users : 902

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

政大機構典藏 > 資訊學院 > 資訊科學系 > 會議論文 > Item 140.119/129022

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/129022

Title:	Enhancing object detection in the dark using U-Net based restoration module
Authors:	彭彥璁 Peng, Yan-Tsung Huang, Y.-T.* Peng, Y.-T. Liao, W.-H.
Contributors:	資科系
Date:	2019-09
Issue Date:	2020-03-02 15:23:15 (UTC+8)
Abstract:	In recent years, we have witnessed the widespread application of deep-learning techniques to various surveillance tasks, including human tracking and counting, abnormal behavior detection, and video segmentation. In most cases, the input images/videos are assumed to possess adequate visual quality to guarantee satisfactory performance. However, accuracy may be adversely affected when the input data are degraded by factors such as excessive noise or poor lighting conditions. In the paper, we develop a deep neural network based on the U-Net architecture that acts as a pre-processing module to restore images/videos with nonuniform light sources to ensure the accuracy of the subsequent object detection process. Experimental results on the VisDrone20 19 dataset [1] demonstrate the effectiveness of the proposed method, achieving a remarkable 5% increase in average recall. We expect the framework to be universally applicable to situations that call for the enhancement of raw input data.
Relation:	2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, University of Taipei
Data Type:	conference
DOI 連結:	https://doi.org/10.1109/AVSS.2019.8909820
DOI:	10.1109/AVSS.2019.8909820
Appears in Collections:	[資訊科學系] 會議論文

Files in This Item:

File	Description	Size	Format
2.pdf		382Kb	Adobe PDF2	408	View/Open

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

Loading...