- 2019/10/10 - Our paper "AnyCharge: An IoT Wireless Charging Service for the Public" has been accepted by IEEE IOT Journal!
- 2018/10/24 - Our paper "VIVID: Virtual Environment for Visual Deep Learning" won the ACM MM 2018 Best Open Source Software Award!
Prof. Kuan-Ting (K. T.) Lai 賴冠廷
Dr. Kuan-Ting Lai received bachelor's degree in Electric Engineering and master's degree in Computer Science from National Taiwan University in 2003 and 2005. After graduation, he joined Quanta Computer as a video ASIC engineer for 4 years, and started to pursue Ph.D. in 2009, under supervision of Prof. Ming-Syan Chen. During 2012-2013, Dr. Lai visited Prof. Shih-Fu Chang’s DVMM lab at Columbia University, and co-developed a large-scale video event detection system with IBM T. J. Watson Research Center. He received his Ph.D. degree in Feb. 2015 and became the VP of technology at Arkados Group. He also co-founded AnyCharge, a wireless charging service provider in Asia. In 2018, Dr. Lai joined the Department of Electronic Engineering at National Taipei University of Technology (臺北科技大學電子工程系) as an Assistant Professor. His research interests include computer vision, deep learning, virtual-to-real learning and Internet of Things. His habit is traveling around the world by joining conferences and making new friends.
VIVID is a photo-realistic simulator that aims to facilitate deep learning for computer vision, which supports different characters: robot, drone, and automobile. The platform can be used for many research fields including deep reinforcement learning, semantic segmentation object recognition and human action recognition. For more details please visit the project's github page.
In this project, we develop a large-scale action detector of drone that can recognize numerous complex human actions such as running, eating, smoking, photo shooting, and create a large-scale dataset to evaluate our algorithm.
Heart attack is one of the leading causes of death in humans. Among them, sudden cardiac arrest is most deadly, causing around 325,000 adult deaths in the United States every year. The portable Automatic External Defibrillator (AED) can automatically detect the patient's heart rhythm pulse and apply an electric shock to restore the heart to work. However, if first aid is not available within 3-5 minutes, the brain will suffer permanent damage. Conversely, if patients can be treated with electric shock within one minute, the success rate of first aid can be as high as 90%. In order to save more lives, we cooperate with the Taiwan Public Defibrillation Development Association to develop 4G drone AED emergency services.
We work together with Feng Chia University to develop a real-time pothole detector on Xilinx FPGA. Additionally, we propose to train detectors in VIVID, and increase the accuracy with less real training photos. Furthermore, our system can connect to CarSim and simulate the response of real cars' suspension systems.
Telecom fraud is one of the most prevalent crimes today and causes most property loss. To identify the roles of the fraudsters, we cooperate with Criminal Investigation Bureau of Taiwan and propose a Telecom Fraud Analysis Model (TFAM).
- Intelligent System Research Center Sofeware Engineer Intern
- Coding 365 Teaching Assistant
- Coding 365 Teaching Assistant
- Exchange student at University of Cincinnati to study industrial big data analysis
- Exchange student at Osaka Prefecture University for studying Computer Science
- Coding 365 Teaching Assistant
- Arima Communications Corp Intern
- AU Optronics Corp Intern
- Google Taiwan Engineering Limited Intern
- HTC Corporation Intern
- Institute for Information Industry Intern
- PROV Technology Corporation, software engineer
- AUTOMATION TECHNOLOGY, EE ,FAE
- shuttle computer, Android BSP engineer
The table is created by Google Scholar on August 20, 2020. For latest information, please visit My Google Scholar Profile.
|AnyCharge: An IoT-Based Wireless Charging Service for the Public|
KT Lai, FC Cheng, SCT Chou, YC Chang, GW Wu, JC Tsai
IEEE Internet of Things Journal 6 (6), 10888-10901, 2019
|An Efficient and Resource-Aware Hashtag Recommendation Using Deep Neural
D Kao, KT Lai, MS Chen
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 150-162, 2019
|VIVID: Virtual Environment for Visual Deep Learning
KT Lai, CC Lin, CY Kang, ME Liao, MS Chen
2018 ACM Multimedia Conference on Multimedia Conference, 1356-1359, 2018
|The privileged sensing framework: A principled approach to improved
AR Marathe, JS Metcalfe, BJ Lance, JR Lukos, D Jangraw, KT Lai, ...
Theoretical Issues in Ergonomics Science 19 (3), 283-320, 2018
|Mining the Networks of Telecommunication Fraud Groups using Social Network
YC Chang, KT Lai, SCT Chou, MS Chen
Advances in Social Networks Analysis and Mining (ASONAM), 2017
|Learning sample specific weights for late fusion
KT Lai, D Liu, SF Chang, MS Chen
IEEE Transactions on Image Processing 24 (9), 2772-2783, 2015
|Recognizing complex events in videos by learning key static-dynamic evidences
KT Lai, D Liu, MS Chen, SF Chang
European Conference on Computer Vision, 675-688, 2014
|Video Event Detection by Inferring Temporal Instance Labels
KT Lai, XY Felix, MS Chen, SF Chang
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, 2014
|Sample-specific late fusion for visual category recognition
D Liu, KT Lai, G Ye, MS Chen, SF Chang
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, 803-810, 2013
|Human action recognition using histogram of oriented gradient of motion history
CP Huang, CH Hsieh, KT Lai, WY Huang
Instrumentation, Measurement, Computer, Communication and Control, 2011 …, 2011
|Orientation histogram of SIFT displacement for recognizing actions in broadcast
KT Lai, MS Chen, CH Hsieh, MF Lai
Visual Information Processing (EUVIP), 2011 3rd European Workshop on, 286-291, 2011
|Human action recognition using key points displacement
KT Lai, CH Hsieh, MF Lai, MS Chen
International Conference on Image and Signal Processing, 439-447, 2010
|Player detection and tracking in broadcast tennis video
YC Jiang, KT Lai, CH Hsieh, MF Lai
Pacific-Rim Symposium on Image and Video Technology, 759-770, 2009
Office AddressComplex Building (綜科館), Room 406-1. No. 1, Sec. 3, Zhongxiao E. Rd., Taipei City, 10643, Taiwan (臺北科技大學)
(+886-2) 2771-2171 Ext. 2275