DC-PSENet: a novel scene text detection method integrating double ResNet-based and changed channels recursive feature pyramid
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Fujian Province
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-03093-5.pdf
Reference57 articles.
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2. Long, S., He, X., Yao, C.: Scene text detection and recognition: the deep learning era. Int. J. Comput. Vis. 129(1), 161–184 (2021). https://doi.org/10.1007/s11263-020-01369-0
3. Kang, J., Ibrayim, M., Hamdulla, A.: Overview of scene text detection and recognition. In: 2022 14th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), pp. 661–666 (2022). https://doi.org/10.1109/ICMTMA54903.2022.00137
4. Chaung, H.-H., Chen, D.-W., Lin, C.-H.: Multi-language text detection and recognition based on deep learning. In: 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), pp. 1–2 (2021). https://doi.org/10.1109/ICCE-TW52618.2021.9603182
5. Tang, Y., Zhu, M., Chen, Z., Wu, C., Chen, B., Li, C., Li, L.: Seismic performance evaluation of recycled aggregate concrete-filled steel tubular columns with field strain detected via a novel mark-free vision method. Structures 37, 426–441 (2022). https://doi.org/10.1016/j.istruc.2021.12.055
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