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Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
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Chang-il Kim, Jinuk Park, Yongju Park, Woojin Jung and Yong-seok Lim
A traffic sign recognition system is crucial for safely operating an autonomous driving car and efficiently managing road facilities. Recent studies on traffic sign recognition tasks show significant advances in terms of accuracy on several benchmarks. H...
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Roopdeep Kaur, Gour Karmakar and Muhammad Imran
In digital image processing, filtering noise is an important step for reconstructing a high-quality image for further processing such as object segmentation, object detection, and object recognition. Various image-denoising approaches, including median, ...
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Jiazhu Dai and Siwei Xiong
Capsule networks are a type of neural network that use the spatial relationship between features to classify images. By capturing the poses and relative positions between features, this network is better able to recognize affine transformation and surpas...
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Zoltán Fazekas, László Gerencsér and Péter Gáspár
A road environment-type (RET) detection function could improve the road awareness of inexperienced car drivers, especially in urban areas, and by doing so, it could slightly raise the urban traffic safety. A pragmatic implementation could make use of sta...
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Yawar Rehman, Hafsa Amanullah, Dost Muhammad Saqib Bhatti, Waqas Tariq Toor, Muhammad Ahmad and Manuel Mazzara
Traffic sign recognition is a key module of autonomous cars and driver assistance systems. Traffic sign detection accuracy and inference time are the two most important parameters. Current methods for traffic sign recognition are very accurate; however, ...
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Shao-Kuo Tai, Christine Dewi, Rung-Ching Chen, Yan-Ting Liu, Xiaoyi Jiang and Hui Yu
In the area of traffic sign detection (TSD) methods, deep learning has been implemented and achieves outstanding performance. The detection of a traffic sign, as it has a dual function in monitoring and directing the driver, is a big concern for driver s...
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Imad Eddine Ibrahim Bekkouch, Youssef Youssry, Rustam Gafarov, Adil Khan and Asad Masood Khattak
Domain adaptation is a sub-field of transfer learning that aims at bridging the dissimilarity gap between different domains by transferring and re-using the knowledge obtained in the source domain to the target domain. Many methods have been proposed to ...
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Alexandros Stergiou, Grigorios Kalliatakis and Christos Chrysoulas
To deal with the richness in visual appearance variation found in real-world data, we propose to synthesise training data capturing these differences for traffic sign recognition. The use of synthetic training data, created from road traffic sign templat...
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Zoltán Fazekas, Gábor Balázs, László Gerencsér, Péter Gáspár
Pág. 341 - 348
Roadworks can be hazardous for both road workers and road users. Even with state-of-the-art safety measures in place, serious accidents do happen there, particularly when drivers do not heed roadwork signs and speed limits. Crashes at roadworks that invo...
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