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Image synthesis with neural networks for traffic sign classification [PDF]
Компьютерная оптика, 2018 In this work, we research the applicability of generative adversarial neural networks for generating training samples for a traffic sign classification task. We consider generative neural networks trained using the Wasserstein metric.
Vladislav Shakhuro, Anton Konushin
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Road images augmentation with synthetic traffic signs using neural networks
Компьютерная оптика, 2021 Traffic sign recognition is a well-researched problem in computer vision. However, the state of the art methods works only for frequent sign classes, which are well represented in training datasets. We consider the task of rare traffic sign detection and
A.S. Konushin +2 more
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An optimization approach for localization refinement of candidate traffic signs [PDF]
, 2017 We propose a localisation refinement approach for candidate traffic signs. Previous traffic sign localisation approaches which place a bounding rectangle around the sign do not always give a compact bounding box, making the subsequent classification ...
Hu, Shimin +3 more
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Towards Enhancing Traffic Sign Recognition through Sliding Windows
Sensors, 2022 Automatic Traffic Sign Detection and Recognition (TSDR) provides drivers with critical information on traffic signs, and it constitutes an enabling condition for autonomous driving.
Muhammad Atif +3 more
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Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods [PDF]
, 2018 This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises ...
Arcos García, Álvaro +2 more
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A robust algorithm for detection and classification of traffic signs in video data [PDF]
, 2012 —The accurate identification and recognition of the traffic signs is a challenging problem as the developed systems have to address a large number of imaging problems such as motion artifacts, various weather conditions, shadows and partial occlusion ...
Bui, Thanh +3 more
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Traffic Sign Classification Using CNN
International Journal for Research in Applied Science and Engineering Technology, 2021 Abstract: With the increasing necessity of autonomous electric vehicles as time passes by, there are a lot of technical prospects within the structure that have a lot of scope for advancement. One such prospect is traffic sign recognition. Several models have already been developed and are in practice but it is evident to everyone within this field ...
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Traffic sign recognition by using chain code [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2012 The Traffic signs are considered as Traffic Safety tools, Because of their role in the organization of traffic and vehicles to insure the safety of the passengers, pedestrians and the structures of traffic signs are very important devices which help the ...
Sundus Ebraheem, Reham Al-Atiwi
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Wasit Journal of Computer and Mathematics Science, 2023 The automatic system for classifying traffic signs is a critical task of Advanced Driver Assistance Systems (ADAS) and a fundamental technique utilized as an integral part of the various vehicles.
Guma Ali +2 more
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Traffic Sign Classification Using CNN
International Journal for Research in Applied Science and Engineering Technology, 2022 Abstract: Traffic signs displayed on the roads play an important role in our lives while driving. They supply critical information, for the road users. This successively requires them to regulate their driving behaviour and ensure that they strictly follow the road regulations currently enforced without causing any trouble to other drivers and ...
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