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Traffic Sign Classification Using Convolutional Neural Network [PDF]
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2021 In today's world, deep learning fields are getting boosted with increasing speed. Lot of innovations and different algorithms are being developed. In field of computer vision, related to autonomous driving sector, traffic signs play an important role to provide real time data of an environment.
null Pranav Kale +4 more
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The Urban Road Traffic Sign Detection & Recognition with Time Space Relationship Model
Sukkur IBA Journal of Emerging Technologies, 2021 Detection and recognition of urban road traffic signs is an important part of the Modern Intelligent Transportation System (ITS). It is a driver support function which can be used to notify and warn the driver for any possible incidence on the current ...
Bhutto Jaseem Ahmed +4 more
doaj +1 more source
Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks
, 2020 Deep neural networks (DNN) are known to be vulnerable to adversarial attacks. Numerous efforts either try to patch weaknesses in trained models, or try to make it difficult or costly to compute adversarial examples that exploit them.
Li, Bo +5 more
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Wireless magnetic sensor network for road traffic monitoring and vehicle classification [PDF]
, 2016 Efficiency of transportation of people and goods is playing a vital role in economic growth. A key component for enabling effective planning of transportation networks is the deployment and operation of autonomous monitoring and traffic analysis tools ...
Allen, Ben +3 more
core +3 more sources
Self-supervised few-shot learning for real-time traffic sign classification
IJAIN (International Journal of Advances in Intelligent Informatics)Although supervised approaches for traffic sign classification have demonstrated excellent performance, they are limited to classifying several traffic signs defined in the training dataset. This prevents them from being applied to different domains, i.e.
Anh-Khoa Tho Nguyen +3 more
doaj +1 more source
Traffic Sign Classification Using CNN
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTThis study presents a novel approach for traffic sign classification leveraging Convolutional Neural Networks (CNNs). With the proliferation of autonomous vehicles and advanced driver assistance systems, accurate and efficient traffic sign recognition is imperative for safe and efficient navigation.
Gautam Arora +4 more
openaire +2 more sources
Traffic Sign Detection and Recognition Using Multi-Frame Embedding of Video-Log Images
Remote Sensing, 2023 The detection and recognition of traffic signs is an essential component of intelligent vehicle perception systems, which use on-board cameras to sense traffic sign information.
Jian Xu, Yuchun Huang, Dakan Ying
doaj +1 more source
Sensors, 2022 In recent years, the development of self-driving cars and their inclusion in our daily life has rapidly transformed from an idea into a reality. One of the main issues that autonomous vehicles must face is the problem of traffic sign detection and ...
Eric Hsueh-Chan Lu +3 more
doaj +1 more source
VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection
, 2019 Although traffic sign detection has been studied for years and great progress has been made with the rise of deep learning technique, there are still many problems remaining to be addressed.
IEEE +8 more
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Image Classification for Traffic Sign Recognition
, 2022 Traffic signs are a crucial part of our road environment. They provide crucial information, sometimes compelling recommendations, to ensure that driving behaviors are adjusted and that any currently enforced traffic regulations are observed. With majority of modern automobiles equipped with an automated driving assistance systems a robust and efficient
Vedant Mahangade +3 more
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