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宋春毅博士、孙煜博士学术报告预告
作者:sxl
发布日期:2011-12-28
浏览次数:
题目:Development of a TV Band Device Prototype for Singapore TV White Space Technology Trial
报告人:宋春毅博士
时 间:12月28日,周三,13:30分
地 点:屏峰校区,广知C楼,511会议室
内容摘要:
Since The Federal Communications Commission (FCC) of USA approved the unlicensed use of TV White Space (TVWS) in November 2008, lots of TVWS utilization related activities have been conducted by regulators and standardization organizations in the other countries and regions. The Infocomm Development Authority (iDA) of Singapore announced a call for TVWS Technology Trial (Singapore Trial) in April 2010 and organized the Singapore Trial in early 2011. The National Institute of Information and Communications Technology (NICT) of Japan, Huawei, I2R of Singapore, MIT and Energy Market participated in the trial. This presentation briefly introduces the TV Band Device (TVBD) prototype developed by NICT for Signapore Trial and the tests conducted by the iDA. Test results for spectrum sensing, Geo-location database access, cognitive radio functionalities and transmitter’s out of band performance will also be presented.
报告人简介:
Dr. Chunyi Song received his Ph.D. in electronic and communication engineering from Waseda University, Tokyo, Japan. He was a Research Associate in Waseda University during 2007-2009. Since August 2009 he has been with National Institute of Information and Communications Technology (NICT), Japan, as an expert researcher. He was the project coordinator in developing the TV band device prototype for Singapore TV White Space Technology Trial, and he currently is coordinating several projects of developing sensing systems for different implementations. He is also involved in IEEE standardization activities including P802.19.1 and 802.22. He is a member of IEEE, IEEE Standards Association and IEICE.
题目: High Level Features in Computer Vision and Pattern Recognition
报告人:孙煜博士
时 间:12月28日,周三,14:00分
地 点:屏峰校区,广知C楼,511会议室
内容摘要:
The high level features are close to the human perception, and they help to improve the object/pattern recognition. In the research projects, two innovative high level features: symmetry ingredients and semantic tokens, are used into the large size database system to improve the indexing, retrieval and recognition. The proposed methods are tested on various public available datasets, and compared to different existing methods to highlight its performance.
报告人简介:Yu Sun,
PhD and MsC: Electrical Engineering, University of California, Riverside, CA, USA.
Bachelor: Telecommunications Engineering, Zhejiang University, Hangzhou, China.
Research topics: Computer Vision, Pattern Recognition, Communication and Control, Machine Learning, Data Mining |
