This paper presents a novel traffic sign dataset, which consists of the Carla Traffic Sign Detection (CTSD), and the Carla Traffic Sign Recognition Dataset ( ...
Using the proposed dataset for training and evaluation, a deep Auto-Encoder algorithm is presented, demonstrating high accuracy in detecting and recognizing the ...
Using the proposed dataset for training and evaluation, a deep Auto-Encoder algorithm is presented, demonstrating high accuracy in detecting and recognizing the ...
In most of the methods, we notice that recognition is based on extraction. This paper proposes a classification technique based on convolutional features in the ...
Synthetic Traffic Signs Dataset for Traffic Sign Detection & Recognition In Distributed Smart Systems ... I. Siniosoglou, P. Sarigiannidis, S. Yannis, A. Khadka, ...
Autonomous Vehicle Navigation: The model can be used in self-driving car systems to recognize traffic signs accurately. This would enable autonomous vehicles to ...
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We proposed a two-stage classification system to overcome the above-mentioned challenges and classify the traffic sign boards efficiently.
Missing: Synthetic Smart
In [28] synthetic traffic signs with poles were generated by computer graphics methods and then improved with a neural network, base on CycleGAN.
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The goal of this research is to precisely detect and recognize traffic signs that are present on the streets using computer vision and deep learning techniques.
To address this problem, we must create a synthetic image to enhance our dataset. We apply deep convolutional generative adversarial networks (DCGAN) and ...