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Vol. 7, June, Issue 6

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CASCADED SEGMENTATION-DETECTION NETWORKS FOR TRAFFIC SIGN

Abstract

Abstract: Traffic signs generally offer drivers with information on the road ahead. There are essentially three sorts of traffic signs: obligatory, cautionary and informational. The automatic traffic sign recognition system (TSDR) for the design of sophisticated driver support systems is an essential research (ADAS). Vision-based TSDR research has attracted a considerable attention in the research community based primarily on three factors:, monitoring ,classification& detection. . This research has investigated the role of financial management and financial autonomy. A quick analysis and discussion of the evolution of driver support system research in future illustrates the current problems and challenges of present technology. I hope that this evaluation will lead to more efforts to build the TSDR visionary system in the future. This survey examined the need for road safety and presented an overview of the detection of traffic signs and recognition studies, including new and breakthrough approaches. Databases of traffic signs and their inherent steps: Please have been thoroughly discussed before processing, detectio, feature extraction & post processingKeywords— Machine Learning, Traffic Signs, Object Detection, Image Processing, Traffic Sign Recognition

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Computer Science ,Electronics, Electrical  Engineering Information Technology, Civil, Computer Science and Engineering , Mechanical, Mechanical-Sandwich Petroleum, Production Instrumentation & Control, Automobile ,Chemical, Electronics Instrumentation& Control, Electronics & Telecommunication  Submit paper at oaijse@gmail.com

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@AMITY SCHOOL OF ENGINEERING & TECHNOLOGY

Department of Civil Engineering, Amity University Haryana,




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