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However, the machine learning methods have been evaluated on clean and challenge-free datasets and overlooked the performance deterioration associated with different challenging conditions (CCs) that obscure the traffic images captured in the wild. In this paper, we look at the TSDR problem under CCs and focus on the performance degradation associated with them. To overcome this, we propose a Convolutional Neural Network (CNN) based TSDR framework with prior enhancement", "lang": "en" }, "license": { "url": "https://creativecommons.org/licenses/by/4.0/", "start": "2023-12-12", "applies_to": "vor" }, "references": [ { "key": "ref1", "doi": "10.1016/j.neucom.2014.12.111", "unstructured": "H. Li, F. Sun, L. Liu and L. Wang, \"A novel traffic sign detection method via color segmentation and robust shape matching\", Neurocomputing, vol. 169, pp. 77-88, Dec. 2015" }, { "key": "ref2", "doi": "10.1007/s11042-016-3321-6", "unstructured": "A. Gudigar, S. Chokkadi, U. Raghavendra and U. R. Acharya, \"Multiple thr esholding and subspace-based approach for detection and recognition of traffic sign\", Multimedia Tools Appl., vol. 76, no. 5, pp. 6973-6991, Feb. 2016" }, { "key": "ref3", "doi": "10.1016/j.eswa.2015.11.018", "unstructured": "S. K. Berkaya, H. Gunduz, O. Ozsen, C. Akinlar and S. Gunal, \"On circular traffic sign detection and recognition\", Expert Syst. Appl., vol. 48, pp. 67-75, Apr. 2016" }, { "key": "ref4", "doi": "10.1109/access.2019.2947069", "unstructured": "A. Mannan, K. Javed, A. Ur Rehman, H. A. Babri and S. K. Noon, \"Classification of Degraded Traffic Signs Using Flexible Mixture Model and Transfer Learning,\" in IEEE Access, vol. 7, pp. 148800-148813, 2019, doi: 10.1109/ACCESS.2019.2947069" }, { "key": "ref5", "doi": "10.1109/access.2020.2975828", "unstructured": "Y. Jin, Y. Fu, W. Wang, J. Guo, C. Ren and X. Xiang, \"Multi-Feature Fusion and Enhancement Single Shot Detector for Traffic Sign Recognition,\" in IEEE Access, vol. 8, pp. 38931-38940, 2020, doi: 10.1109/ACCESS.2020.2975828" }, { "key": "ref6", "doi": "10.1109/access.2018.2884826", "unstructured": "C. Gámez Serna and Y. Ruichek, \"Classification of Traffic Signs: The European Dataset,\" in IEEE Access, vol. 6, pp. 78136-78148, 2018, doi: 10.1109/ACCESS.2018.2884826" }, { "key": "ref7", "doi": "10.1109/sitis.2018.00109", "unstructured": "D. Varytimidis, F. Alonso-Fernandez, B. Duran and C. Englund, \"Action an d Intention Recognition of Pedestrians in Urban Traffic,\" 2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2018, pp. 676-682, doi: 10.1109/SITIS.2018.00109" }, { "key": "ref8", "doi": "10.1109/access.2019.2912311", "unstructured": "X. Bangquan and W. 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