Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)

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Current Research on Convolutional Neural Network for Unmanned Driving

Authors
Xinyue Zhang1, *
1College of International, Hebei University, Tianjin, China
*Corresponding author.
Corresponding Author
Xinyue Zhang
Available Online 14 February 2024.
DOI
10.2991/978-94-6463-370-2_43How to use a DOI?
Keywords
Artificial neural network; Unmanned driving; Identification; Scene recognition
Abstract

With the development of artificial intelligence and the upgrading of traditional cars, artificial neural networks have great potential in unmanned driving technology. Academics are paying increasingly close attention to computer vision research, and applications based on artificial neural networks are slowly but surely making their way into everyday life. In response to this situation, convolutional neural network models have good adaptability. Convolutional neural networks can be quite effective in identifying features and categorizing images. Technology for autonomous vehicles may recognize obstructions, road signs, and driver tiredness. Even when an image is translated, scaled, rotated, or thickened locally or globally, it may still produce the matching recognized information with high resilience and interference resistance.This article studies the following principal contents: extracting and processing color and shape segmentation regions, researching algorithms for identifying traffic signs, detecting multiple target criticalpoints based on Mask R-CNN, and comparing the performance of Mask R-CNN and Mask R-CNN combined with critical point detection.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
Series
Advances in Intelligent Systems Research
Publication Date
14 February 2024
ISBN
10.2991/978-94-6463-370-2_43
ISSN
1951-6851
DOI
10.2991/978-94-6463-370-2_43How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Xinyue Zhang
PY  - 2024
DA  - 2024/02/14
TI  - Current Research on Convolutional Neural Network for Unmanned Driving
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 411
EP  - 420
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_43
DO  - 10.2991/978-94-6463-370-2_43
ID  - Zhang2024
ER  -