Traffic signs recognition system using convolutional neural network in autonomous vehicles and self-driving vehicles, has convolutional neural network i.e. image classifier for capturing image as input to look for aspects in image to differentiate one from another
	KALIYAMURTHIE K P; CHAND G K; JAYANTHI Y; BHARGAV K; ADITYA P T; RAJABHUSHANAM C
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069697-A
成果简介	NOVELTY - The system has driverless cars which are automated to identify the traffic signals and move on the roads following the safety measures. A deep neural network model classifies traffic signs present in an image into different categories, uploads an image, identifies the traffic symbol and provides output. A convolutional neural network (CNN) is a class of deep learning algorithm and is an image classifier which captures image as an input to look for various aspects in the image to differentiate one from another. Keras is an open-source software library, comprises a Python(High-level programming language) interface for artificial neural networks, develops and evaluates the deep learning model and acts as an interface for a Tensor flow library (Open source software library). USE - Traffic signs recognition system using CNN in autonomous vehicles and self-driving vehicles. ADVANTAGE - The system understands and follows all the traffic rules for the safety of passengers.
IPC 分类号	G06K-009/62 ; G06N-020/00 ; G06N-003/08 ; G06V-020/58
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19829
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	KALIYAMURTHIE K P,CHAND G K,JAYANTHI Y,et al. Traffic signs recognition system using convolutional neural network in autonomous vehicles and self-driving vehicles, has convolutional neural network i.e. image classifier for capturing image as input to look for aspects in image to differentiate one from another. IN202341069697-A[P]. 2023.

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