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Chapter | Dates | Distinguished Lecturer | Lecture Details |
---|---|---|---|
Vancouver | April 21, 2016 | Min Wu (University of Maryland, USA) |
Xu, PingMei (Princeton University), “Understanding and predicting human visual attention” (2016) Advisor: Kulkarni, Sanjeev ; Xiao, Jianxiong
Liu, Yang, (Lehigh University), “Reliable and Efficient Transmission of Signals: Coding Design, Beamforming Optimization and Multi-Point Cooperation” (2016) Advisor: Li, Jing
Please refer to the following webpage for the latest updates on upcoming conferences in Signal Processing.
http://www.signalprocessingsociety.org/conferences/upcoming-conferences/
Now IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form at the related TC section pages.
For our February 2016 issue, we cover recent patents dealing with range image formation and processing.
The Board of Governors of the IEEE Signal Processing Society (SPS) elected one new officer who will start his term on 1 January 2017:
In accordance with the Bylaws of the IEEE Signal Processing Society, the membership will elect, by direct ballot, THREE Members-at-Large to the Board of Governors (BoG) for three-year terms commencing 1 January 2017 and ending 31 December 2019, as well as ONE Regional Director-at-Large each for the corresponding regions: Regions 1-6 (USA) and Region 8 (Europe, Middle East, Africa) for two-year terms commencing 1 January 2017 and ending 31 December 2018.
The IEEE Signal Processing Society invites nominations for the 2017 Class of SPS Distinguished Lecturers (DLs). The deadline for nominations is 31 May 2016. Each year, up to ten (10) technically diverse and geographically dispersed individuals serve as IEEE Signal Processing Society Distinguished Lecturers.
Welcome to the Spring 2016 edition of the IEEE Speech and Language Processing Technical Committee's Newsletter! This issue of the newsletter includes 5 articles and announcements from 6 contributors, including our own staff reporters and editors. Thank you all for your contributions!
Many modern signal processing (SP) methods rely very strongly on probability and statistics tools to solve problems; for example, they use stochastic models to represent the data observation process and the prior knowledge available and they obtain solutions by performing statistical inference (e.g., using maximum likelihood or Bayesian strategies).
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