A Novel Convolutional Neural Network Based Architecture for Object Detection and Recognition with an Application to Traffic Sign Recognition from Road Scenes-Reference-Cited by-同舟云学术

A Novel Convolutional Neural Network Based Architecture for Object Detection and Recognition with an Application to Traffic Sign Recognition from Road Scenes

Published:2022-06 Issue:2 Volume:32 Page:351-362
ISSN:1054-6618
Container-title:Pattern Recognition and Image Analysis
language:en
Short-container-title:Pattern Recognit. Image Anal.

Author:

Karthika R.,Parameswaran Latha

Publisher

Pleiades Publishing Ltd

Subject

Computer Vision and Pattern Recognition

Link

https://link.springer.com/content/pdf/10.1134/S1054661822020110.pdf

Reference31 articles.

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3. Á. Arcos-García, J. A. Álvarez-García, and L. M. Soria-Morillo, “Evaluation of deep neural networks for traffic sign detection systems,” Neurocomputing 316, 332–344 (2018). https://doi.org/10.1016/j.neucom.2018.08.009

4. X. Changzhen, W. Cong, M. Weixin, and S. Yanmei, “A traffic sign detection algorithm based on deep convolutional neural network,” in IEEE Int. Conf. on Signal and Image Processing (ICSIP), Beijing, 2016 (IEEE, 2016), pp. 676–679. https://doi.org/10.1109/SIPROCESS.2016.7888348

5. J. Choi, D. Chun, H. Kim, and H.-J. Lee, “Gaussian YOLOv3: An accurate and fast object detector using localization uncertainty for autonomous driving,” in IEEE/CVF Int. Conf. on Computer Vision (ICCV), Seoul, 2019 (IEEE, 2019), pp. 502–511. https://doi.org/10.1109/ICCV.2019.00059

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