As a service to the IEEE Signal Processing Society (SPS) community, the SPS Challenge Program offers support to challenge organizers. Submit a challenge proposal, due 1 September 2023.

The Signal Processing Society (SPS) conducts webinars presented by professionals in the field of signal processing and related technologies on an ongoing basis. Webinars are also hosted periodically by SPS Technical Committees, and other network of communities. Visit the Upcoming Events page to see a list of our upcoming webinars and join us! Visit theSPS BLOG for more related content on a regular basis!

Good news! You asked and we listened! With more than one issue being planned in 2024 for the new JSTSP AI/ML Special Series, we will start to accept rolling submissions. 

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 related to a particular TC field. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and selecting a particular TC.

Pierre Comon is currently Emeritus Research Director with CNRS. He received the Doctorate degree in 1985 from the University of Grenoble, and the Habilitation to Lead Researches in 1995, from the University of Nice, France. 

The IEEE Signal Processing Society (SPS) invites nominations for the positions of Awards Board Chair and Fellow Evaluation Committee - Chair and Vice Chair. Nominations should be received no later than 13 July 2023.

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 related to a particular TC field. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and selecting a particular TC.

A coarse-to-fine SR CNN (CFSRCNN) consisting of a stack of feature extraction blocks (FEBs), an enhancement block (EB), a construction block (CB) and, a feature refinement block (FRB) is proposed to learn a robust SR model.