The purpose of the Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC) is to promote and guide the advancement of the field of image, video, and multidimensional signal processing.
The 16th International Workshop on Acoustic Signal Enhancement (IWAENC) will be held at Hitotsubashi Hall in Tokyo, Japan, on September 17 – 20, 2018. IWAENC was established in 1993, originally as the International Workshop on Acoustic Echo and Noise Control (this is how the abbreviation IWAENC came into use). It is the leading workshop in the signal processing community addressing theoretical and technical issues related to acoustic and speech signal acquisition and processing.
Important Dates for submitting SPS Travel Grant Application for ICIP 2017
Application Open: May 8, 2017
Application and Recommendation Letter Deadline: May 24, 2017 at 12:00 PM EDT
Application Closed: May 24, 2017 at 12:00 PM EDT
Decisions Announced: June 2, 2017
ICIP Travel Grant Application Form: Application Form (link is externa
The Technical Committee on Information Forensics and Security (IFS-TC) is inviting proposals for its flagship workshop WIFS, to be held in Fall/Winter2018. The workshop is technically co-sponsored by the IEEE Signal Processing Society (SPS) and the Biometrics Council (BMC). The proposal
should target an audience around 120-160 attendees. Interested groups and individuals are strongly encouraged to approach the members of the IEEE IFS-TC WIFS subcommittee to openly discuss and improve their proposals1. The proposals should be complete and detailed.
EAB is launching a call for nominations for the eleventh European Biometrics Research and Industry Awards. These prestigious awards are granted annually to individuals who have been judged by a panel of internationally respected experts to be making a significant contribution to the field of biometrics research and innovations in Europe.
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.