An Improved YOLOv8 Model for Traffic Sign Detection and Classification-Reference-Cited by-同舟云学术

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An Improved YOLOv8 Model for Traffic Sign Detection and Classification

Published:2024-03-01 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 3rd International Conference for Innovation in Technology (INOCON)
language:
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Author:

Kaur Arshleen¹,Kukreja Vinay¹,Thapliyal Nitin²,Aeri Manisha²,Sharma Rishabh³,Hariharan Shanmugasundaram⁴

Affiliation:

1. Chitkara University,Chitkara University Institute of Engineering and Technology,Punjab,India

2. Graphic Era Hill University,Computer Science and Engineering,Dehradun,Uttrakhand,India,248002

3. Graphic Era Deemed to be University,Computer Science and Engineering,Dehradun,Uttarakhand,India

4. Vardhaman College of Engineering,Department of Computer Science and Engineering,Hyderabad,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10511271/10511093/10511576.pdf?arnumber=10511576

Reference20 articles.

1. Improved YOLOv5 network for real-time multi-scale traffic sign detection

2. Indian traffic sign detection and recognition using deep learning

3. Traffic sign detection in unconstrained environment using improved YOLOv4

4. Hispa Rice Disease Classification using Convolutional Neural Network

5. Road Traffic Sign Detection Method Based on RTS R-CNN Instance Segmentation Network

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