Research on detection and classification of traffic signs with data augmentation
Author:
Funder
Zhejiang Province Public Welfare Technology Application Research Project
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-14895-z.pdf
Reference29 articles.
1. Abdi L, Meddeb A (2018) Spatially Enhanced Bags of Visual Words Representation to Improve Traffic Signs Recognition[J]. J Signal Process Syst Signal Image Vid Technol 90(12):1729–1741
2. Arcos-Garcia A, Alvarez-Garcia JA, Soria-Morillo LM (2018) Evaluation of deep neural networks for traffic sign detection systems[J]. Neurocomputing 316:332–344
3. Chen LC, Hermans A, Papandreou G et al (2018) MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features[C]. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp 4013–4022. https://doi.org/10.1109/CVPR.2018.00422
4. Cheng P, Liu W, Zhang Y et al. (2018) LOCO: local context based faster R-CNN for small traffic sign detection[J]. MultiMed Model 10704:329–341
5. Dewi C, Chen R-C, Tai S-K (2020) Evaluation of robust spatial pyramid pooling based on convolutional neural network for traffic sign recognition system[J]. Electron 9(6):889
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