https://scholars.lib.ntu.edu.tw/handle/123456789/502328
標題: | Patch-based face hallucination with multitask deep neural network | 作者: | Ko, W.-J. SHAO-YI CHIEN |
關鍵字: | deep learning; Face hallucination; superresolution | 公開日期: | 2016 | 卷: | 2016-August | 來源出版物: | Proceedings - IEEE International Conference on Multimedia and Expo | 摘要: | Face hallucination technique generates high-resolution face images from low-resolution ones. In this paper, we propose a patch based multitask deep learning method for face hallucination, which is robust to blurring of images. Our method is based on fully connected feedforward neural network, and the weights of the final layers are fine-tuned separately on different clusters of patches. Experimental results show that our system outperforms the prior state-of-the-art methods by a significant margin, while using less testing computation time. © 2016 IEEE. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/502328 | ISSN: | 19457871 | DOI: | 10.1109/ICME.2016.7552975 | SDG/關鍵字: | Feedforward neural networks; Computation time; Deep learning; Deep neural networks; Face hallucination; High resolution; Low resolution; State-of-the-art methods; Super resolution; Face recognition |
顯示於: | 電機工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。