Generate Realistic Traffic Sign Image using Deep Convolutional Generative Adversarial Networks-Reference-Cited by-同舟云学术

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Generate Realistic Traffic Sign Image using Deep Convolutional Generative Adversarial Networks

Published:2021-01-30 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Conference on Dependable and Secure Computing (DSC)
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Author:

Liu Yan-Ting¹,Chen Rung-Ching¹,Dewi Christine²

Affiliation:

1. Chaoyang University of Technology,Department of Information Management,Taichung,Taiwan

2. Chaoyang University of Technology Taichung, Taiwan Faculty of Information Technology, Satya Wacana Christian University,Department of Information Management,Salatiga,Indonesia

Funder

Ministry of Science and Technology, Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9346211/9346228/09346266.pdf?arnumber=9346266

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Generative Adversarial Network for Synthetic Image Generation Method: Review, Analysis, and Perspective;Applications of Generative AI;2024

2. Contrast Stretching For Automatic Road Marking Detection at Night With YOLOv5;2023 12th International Conference on Awareness Science and Technology (iCAST);2023-11-09

3. Traffic Sign Repositories: Bridging the Gap Between Real and Synthetic Data;Communications in Computer and Information Science;2023

4. Real time road sign detection based on YOLO and Swift;International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022);2022-10-13

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