This study provides a systematic review of the field of traffic sign recognition. Thirty-nine papers relevant to this study were manually selected for exploration from four well-known databases (IEEE Xplore, ScienceDirect, Scopus, and Google Scholar). Five questions were proposed to describe general...
Road-Sign Detection and Recognition Based on Support Vector Machines This paper presents an automatic road-sign detection and recognition system based on support vector machines (SVMs). In automatic traffic-sign maintenance ... S Maldonado-Bascon,S Lafuente-Arroyo,P Gil-Jimenez,... - 《IEEE ...
CURE-TSR: Challenging Unreal and Real Environments for Traffic Sign Recognition - olivesgatech/CURE-TSR
Soll, M. (2019). InformatiCup Competition 2019: Fooling Traffic Sign Recognition. In: Benzmüller, C., Stuckenschmidt, H. (eds) KI 2019: Advances in Artificial Intelligence. KI 2019. Lecture Notes in Computer Science(), vol 11793. Springer, Cham. https://doi.org/10.1007/978-3-030-301...
Sign in to download hi-res image Fig. 5.The schematic view of the OpenTCP. The architecture mainly includes two main parts: (a) Oracle is a controller application that is responsible for collecting information about the underlying devices and finding suitable changes for TCP according to a pred...
Lane-based traffic arrival pattern estimation using license plate recognition data IEEE Intell. Transp. Syst. Mag. (2021) In press Google Scholar [104] Tan C., Liu L., Wu H., Cao Y., Tang K. Fuzing license plate recognition data and vehicle trajectory data for lane-based queue length...
Improving callsign recognition with air-surveillance data in air-traffic communication Automatic Speech Recognition Benchmark for Air-Traffic Communications How to cite us If you use this code for your research, please cite our papers with the following bibtex items: # article 1 - MAIN @article{...
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IEEE Conference on Computer Vision & Pattern Recognition, Miami, FL (2009), pp. 248-255 Google Scholar Guo et al., 2019 S. Guo, Y. Lin, S. Li, Z. Chen, H. Wan Deep spatial-temporal 3D convolutional neural networks for traffic data forecasting IEEE Trans. Intell. Transport. Syst.,...
Applying Machine Learning Techniques to Transportation Mode Recognition Using Mobile Phone Sensor Data IEEE Transactions on Intelligent Transportation Systems, 16 (5) (2015), pp. 2406-2417, 10.1109/TITS.2015.2405759 View in ScopusGoogle Scholar Jenkins et al., 2017 Jenkins, S., Codjoe, J., Alec...