References
- H. J. Son & S. H. Kim. (2007). Machine Learning in Character Pattern Recognition. Communications of the Korean Institute of Information Scientists and Engineers, 25(3), 12-20. pISSN : 1229-6821
- K. S. Son, J. W. Kim & J. H. Lim. (2019). Convergence CCTV camera embedded with Deep Learning SW technology. Journal of the Korea Convergence Society, 10(1), 103-113. DOI : 10.15207/JKCS.2019.10.1.103
- Q. Ye & D. Doermann. (2014). Text Detection and Recognition in Imagery: A Survey. IEEE Transactions On Patern Analysis And Machine Inteligence, 37(7), 1480-1500. DOI : 10.1109/TPAMI.2014.2366765
- K. K. Kim, Y. Hur, G. M. Kim, W. H. Yu & H. S. Lim. (2017). Detail Focused Image Classifier Model for Traditional Images. Journal of the Korea Convergence Society, 8(12), 85-92. DOI : 10.15207/JKCS.2017.8.12.085
- J. S. Hwang, H. H. Jeon, S. H. Kim, & K. K. Kwon. (2017). OCR image recognition rate digital solution for prescription scanning. Proceedings of Korean Institute of Information Technology Conference. (pp. 379-381).
- S. H. Lee, J. H. Jeon, H. S. Hong, D. H. Kang & M. H. Park. (2017). Korean Prescription Character Recognition System Using OCR Technology. Proceedings of The Korean Institute of Information Scientists and Engineers Conference. (pp. 362-364).
- C. Y. Suen, S. Mori, H. C. Rim & P. S. P. Wang. (1998). Intriguing Aspects of Oriental Languages. International Journal of Pattern Recognition and Artificial Intelligence, 12(1), 5-29. DOI : 10.1142/S0218001498000038
- M. K. Kim & K. H. Lee. (1999). Design of Receipt Automation System Using OCR. Proceedings of The Korean Institute of Information Scientists and Engineers Conference. (pp. 531-533).
- S. W. Lee. (2002). Study on the selecting optimal artificial neural networks model prior to forecasting stock. master thesis, Inje University, Gyeongsangnam-do.
- K. D. Kim & Y. H. Kim. (2017). A Survey on Oil Spill and Weather Forecast Using Machine Learning Based on Neural Networks and Statistical Methods. Journal of the Korea Convergence Society, 8(10), 1-8. DOI : 10.15207/JKCS.2017.8.10.001
- Q. Li, W. Cai, X. Wang, Y. Zhou, D. D. Feng & M. Chen. (2014). Medical image classification with convolutional neural network. International Conference on Control Automation Robotics & Vision. (pp. 844-848). DOI : 10.1109/ICARCV.2014.7064414
- O. Janssens et al. (2016). Convolutional Neural Network Based Fault Detection for Rotating Machinery. Journal of Sound and Vibration, 377, 331-345. DOI : 10.1016/J.JSV.2016.05.027
- Y. Lecun, L. Bottou, Y. Bengio & P. Haffner. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278-2324. DOI : 10.1109/5.726791
- P. Liu, X. Qiu & X. Huang. (2016). Recurrent Neural Network for Text Classification with Multi-Task Learning. Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence.
- B. Shi, X. Bai & C. Yao. (2017). An End-to-End Trainable Neural Network for Image-Based Sequence Recognition and Its Application to Scene Text Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(11), 2297-2304. DOI : 10.1109/TPAMI.2016.2646371
- Y. G. Kim & E. Y. Cha. (2016). Streamlined GoogLeNet Algorithm Based on CNN for Korean Character Recognition. Journal of the Korea Institute of Information and Communication Engineering, 20(9), 1657-1685. DOI : 10.6109/jkiice.2016.20.9.1657
- B. Shi, M. Yang, X. Wang. P. Lyu, C. Yao & X. Bai (2019). ASTER: An Attentional Scene Text Recognizer with Flexible Rectification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(9), 2035-2048. DOI : 10.1109/TPAMI.2018.2848939