Each year, the IEEE Board of Directors confers the grade of Fellow on up to one-tenth of one percent of the voting members. To qualify for consideration, an individual must have been a Member, normally for five years or more, and a Senior Member at the time for nomination to Fellow.

The IEEE SPS congratulates the following SPS members who will receive the Society’s prestigious awards during ICASSP 2025 in India.

We are excited to announce that registration for the IEEE International Symposium on Biomedical Imaging (ISBI) 2025 is now open! Join us from April 14-17, 2025, in Houston, TX, USA for the premier forum that brings together researchers and practitioners at the forefront of biomedical imaging science and technology.

The IEEE Signal Processing Society (SPS) announces the 2025 Class of Distinguished Lecturers and Distinguished Industry Speakers for the term of 1 January 2025 to 31 December 2026, which are noted below.

The IEEE Signal Processing Society Kolkata Chapter has been selected as the recipient of the 2024 Chapter of the Year Award!

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 the SPS BLOG for more related content on a regular basis!

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.

The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.

An occlusion-aware model for gait video processing uses SMPL-based human mesh models and machine learning to achieve superior recognition in challenging surveillance videos.

Electromagnetic inverse scattering problems (ISPs) are crucial in noninvasive imaging but challenging due to nonlinearity and computational costs. This blog explores machine learning-based ISP solvers with physics-guided loss functions, emphasizing the role of near-field priors and multiple-scattering effects. Numerical experiments highlight the advantages and limitations of these approaches.