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The Latest News, Articles, and Events in Signal Processing
The IEEE Signal Processing Society invites all SPS Members to collaborate with their local Chapter in submitting a proposal for a Seasonal School, Forum, Regional Meeting, or Chapter Initiative event scheduled between April 2025 and September 2025.
Date: 20 November 2024
Time: 2:00 PM (Paris Time)
Presenter(s): Bastian Grossenbacher Rieck
Date: 6-10 December 2025
Location: Honolulu, HI, USA
Paper Submission Deadline: Coming soon
Website Link: Coming soon
Date: 6 December 2024
Chapter: Santa Clara Valley Chapter
Chapter Chair: Peng Zhang
Title: Promoting Yourself: How to appeal accomplishments for member-level elevation, award nomination, and promotion in the company
Three new Members-at-Large will take their seats on the IEEE Signal Processing Society Board of Governors beginning 1 January 2023 and will serve until 31 December 2025. Seven candidates competed for the three Member-at-Large positions.
The IEEE Signal Processing Society (SPS) is proud to announce the 2024 class of SPS Scholarship recipients!
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.
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!
Dr. Yan Ye is currently the Head of Video Technology Lab of Alibaba’s Damo Academy in Sunnyvale California. Prior to Alibaba, she held various technical and management and positions at InterDigital, Dolby Laboratories, and Qualcomm.
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.
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.
IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society.
Nominations are due 15 January annually for the IEEE Technical Field Awards (TFAs). Download nomination forms and award-specific criteria.
Date: 14 November 2024
Time: 7:30 AM ET (New York Time)
Presenter(s): Dr. Tomohiro Nakatani
Date: 17 December 2024
Time: 10:00 AM ET (New York Time)
Presenter(s): Dr. Hung-yi Lee
As I take on the President of the Signal Processing Society (SPS) role, I am excited to connect with you through this column. I look forward to introducing myself and inviting you, the members, to join our volunteers in shaping our shared future.
We opened the year with the theme of “embracing interdisciplinarity,” emphasizing the fact that signal processing naturally builds bridges across different domains and disciplines. The front cover image of an organic bridge across mature trees giving birth to a sapling helped convey our message. After two special issues (two parts of one special issue), we come back to you with an issue comprised of feature articles and columns, which all reinforce the message in our first issue of 2024.
The flexibility and dexterity of human limbs rely on the processing of a vast quantity of signals within the sensory-motor networks in the brain and spinal cord, distilled into stimuli that govern the commands and movements. Hence, the use of assistive devices, such as robotic limbs or exoskeletons, is critically dependent on the processing of a large number of heterogeneous signals to mimic natural movements.
Deep learning, in general, focuses on training a neural network from large labeled datasets. Yet, in many cases, there is value in training a network just from the input at hand. This is particularly relevant in many signal and image processing problems where training data are scarce and diversity is large on the one hand, and on the other, there is a lot of structure in the data that can be exploited.
By “social learning,” in this article we refer to mechanisms for opinion formation and decision making over graphs and the study of how agents’ decisions evolve dynamically through interactions with neighbors and the environment. The study of social learning strategies is critical for at least two reasons.
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