Underground Garage Patrol Based on Road Marking Recognition by Keras and Tensorflow
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Published:2023-02-13
Issue:4
Volume:13
Page:2385
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Gan Jianwen1, Zhang Longqing2ORCID, Chen Hongming3ORCID, Bai Liping1, Zhang Xinwei2, Yang Lei2, Zhang Yanghong2
Affiliation:
1. Department of Computer Science, Macau University of Science and Technology, Taipa, Macau, China 2. Department of Computer Science, Guangdong University of Science and Technology, Dongguan 523070, China 3. Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022, China
Abstract
The purpose of this study was to design an unmanned patrol service in combination with artificial intelligence technology to solve the problem of underground vehicle patrol. This design used the Raspberry Pi development board, L298N driver chip, Raspberry Pi camera, and other major hardware equipment to transform the remote control car. This design used Python as the programming language. By writing Python code, the car could be driven under the control of the computer keyboard and the camera was turned on for data collection. The Keras neural network library was used to quickly build a neural network model, the collected data was used to train the model, and the model was finally generated. The model was placed in the TensorFlow system for processing, and the car could travel in a preset track for unmanned driving.
Funder
Guangdong General University Young Innovative Talents Guangdong University of Science and Technology Quality Engineering Special Projects in Key Areas for General Universities in Guangdong Province National key research and development program of China Natural Science Foundation of Guangdong Province of China Innovation and Improve School Project from Guangdong University of Science and Technology College Students Innovation Training Program held by Guangdong University of Science and Technology
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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