DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-9,Issue-3 ( Mar, 2021 ) | |||||||||
Paper Title |
CNN as Traffic Sings and Vehicle Classification Model: Model Analysis and Optimizing based on Tensorflow | |||||||||
Author Name |
Malicehnkoviktor, Han Honggui | |||||||||
Affilition |
Department of Information, Beijing University of Technology, China | |||||||||
Pages |
6-11 | |||||||||
Abstract |
Object detection and classification are among the most investigated types of projects and applicable in a wide range of jobs. One of the main goal is to create such a training model, which contains state-of-the-art technologies and methods with well-tuned parameters, and can be used to scale the project and implement it in real time. This will make it possible, with a luck of a big team, to create an unmanned vehicle that can recognize obstacles and take the necessary actions to avoid accidents. An essential criterion for creating such a model is to use approaches, with a clear analysis (using Tensorboard analysis) and understanding of the significance of each parameter. So we create a unique model that will be as stress-resistant as possible. Proposed article is a part of research of implementing artificial intelligence in different directions of the industry, developed in the laboratory of BJUT. Keywords - CNN, Object Classification, Tensorflow, Tensorboard, Traffic Sings - Vehicles | |||||||||
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