Scope The Machine Learning for Signal Processing Technical Committee (MLSP TC) is at the interface between theory and application, developing novel theoretically-inspired methodologies targeting both longstanding and emergent signal processing applications. Central to MLSP is on-line/adaptive nonlinear signal processing and data-driven learning methodologies.
CALL FOR PROPOSALS Deadline: Monday, October 9th, 2017.
One-page proposals are invited for the annual Frederick Jelinek Memorial Workshop in Speech and Language Technology. Proposals should aim to advance the state of the art in any of the various fields of Human Language Technology (HLT) or related areas of Machine Intelligence, including Computer Vision and Healthcare.
For our October 2017 issue, we cover recent patents granted in the area of compressed sensing.
Patent no. 9,755,714 proposes methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO LTE wireless network include receiving training signals from a plurality of users, estimating a maximum delay spread for the received data according to a coherence bandwidth...
The Department of Electrical and Computer Engineering (ECE) at the National University of Singapore (NUS) is offering positions for postdoctoral fellows who will work closely with Dr. Vincent Tan at the intersection of information theory, statistical signal processing, and machine learning.
A video tutorial on Multimedia Forensics, by Roberto Caldelli and Rabab Ward, has been recently presented at ICIP 2017.
The video has been produced by IEEE-SPS and IEEE-IFS TC in cooperation with UBC Studios with the intent to widely divulge what Multimedia Forensics can do and its applications.
The video can be accessed through:
http://signalprocessingsociety.org/our-story/multimedia-content
https://youtu.be/NRRzs0bB0a0