Acknowledgement
This work was conducted as a part of the research project of "Development of IoT Infrastructure Technology for Smart Port" and in part the research project of " Development of automatic screening and hybrid detection system for hazardous material detecting in port container" (20200611) financially supported by the Ministry of Oceans and Fisheries
References
- Song, J. W. (2015). Container BIC-code region extraction and recognition method using multiple thresholding, Master Thesis. Graduate School of Chungbuk National University, Cheongju, Korea.
- Max J., Karen S., Andrew Z. and koray k. (2015). Spatial Transformer Networks, Neural Information Processing Systems, 28, 2017-2025.
- Francois C. (2017). Xception: Deep Learning with Depthwise Separable Convolutions, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1800-1807, https://doi.org/10.1109/CVPR.2017.195.
- Christian S., Vincent V., Sergey l., Jon S and Zbigniew W. (2016). Rethinking the Inception Architecture for Computer Vision, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2818-2826, https://doi.org/10.1109/CVPR.2016.308.
- Peter J. H. (1964). Robust Estimation of a Location Parameter, The Annals of Mathmatical Statistics, 53 (1), 73-101, https://doi.org/10.1214/aoms/1177703732
- Leon A. G., Alexander S. E. and Matthias B. (2016). Image Style Transfer Using Convolutional Neural Networks, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2414-2423, https://doi.org/10.1109/CVPR.2016.265.
- Karen S. and Andrew Z. (2015). Very Deep Convolutional Networks for Large-Scale Image Recognition, CoRR, abs/1409.1556.