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Computer Vision, Image Processing, and Pattern Recognition
To be able to automatically capture, process, analyze, and use image and video contents are getting more and more important these days, thanks to the improving computing power, the growing number of cameras, and the fast-increasing use of mobile devices. Our focus is to make computers more intelligent such that they can automatically analyze and learn from image data, recognize objects, and understand image contents automatically. We expect these technologies will greatly make our life more rich, safe, and convenient.
Our research field covers a wide array of topics related to images. Image processing includes the enhancement, restoration, segmentation, compression, and watermarking techniques. A more advanced example is adaptive image scaling that intelligently provides good-quality viewing for various display devices. Computer vision covers all kinds of analysis of visual contents, e.g., camera calibration, three-dimensional modeling, automatic localization and environment learning in stereo vision, the detection and recognition of persons, objects, and events in surveillance systems, as well as video content analysis and many other techniques. Pattern recognition is concerned with the techniques for automatic classification and clustering of data, which have many applications in computer vision.
|王才沛 Tsai-Pei Wang||王昱舜 Yu-Shuen Wang||林文杰 Wen-Chieh Lin||林正中 Cheng-Chung Lin||林奕成 I-Chen Lin|
|林彥宇 Yen-Yu Lin||邱維辰 Wei-Chen Chiu||莊仁輝 Jen-Hui Chuang||莊榮宏 Jung-Hong Chuang||陳永昇 Yong-Sheng Chen|
|陳冠文 Kuan-Wen Chen||陳奕廷 Yi-Ting Chen||彭文孝 Wen-Hsiao Peng||黃敬群 Ching-Chun Huang||蔡文祥 Wen-Hsiang Tsai|
|蔡文錦 W. J. Tsai||蕭旭峰 Hsu-Feng Hsiao||魏群樹 Chun-Shu Wei||劉育綸 Yu-Lun Lin|