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The Latest News, Articles, and Events in Signal Processing
Date: 30 January 2024
Time: 8:00 AM ET (New York Time)
Presenter(s): Dr. Congli Wang, Dr. Wolfgang Heidrich
Manuscript Due: 31 July 2024
Publication Date: March 2025
Date: 6 March 2024
Time: 10:00 AM ET (New York Time)
Presenter(s): Javier Escudero
Date: 11 January 2024
Time: 10:00 AM ET (New York Time)
Presenter(s): Dr. Enrico Magli
Date: 7 February 2024
Time: 8:00 AM ET (New York Time)
Presenter(s): Dr. Athina P. Petropulu, Mr. Zhaoyi Xu
Date: 9 January 2024
Time: 8:00 AM ET (New York Time)
Presenter(s): Dr. Ran He
Date: 29 January 2024
Time: 10:00 AM ET (New York Time)
Speaker(s): Dr. Joseph Tabrikian
This paper presents a neural-enhanced probabilistic model and corresponding factor graph-based sum-product algorithm for robust localization and tracking in multipath-prone environments. The introduced hybrid probabilistic model consists of physics-based and data-driven measurement models capturing the information contained in both, the line-of-sight (LOS) component as well as in multipath components (NLOS components). The physics-based and data-driven models are embedded in a joint Bayesian framework allowing to derive from first principles a factor graph-based algorithm that fuses the information of these models.
Neural networks have achieved state-of-the-art performance on the task of acoustic Direction-of-Arrival (DOA) estimation using microphone arrays. Neural models can be classified as end-to-end or hybrid, each class showing advantages and disadvantages. This work introduces Neural-SRP, an end-to-end neural network architecture for DOA estimation inspired by the classical Steered Response Power (SRP) method, which overcomes limitations of current neural models.
In this article, we consider using time-of-arrival (TOA) measurements from a single moving receiver to locate a moving target at constant velocity that emits a periodic signal with unknown signal period. First, we give the TOA measurement model and deduce the Cram
Synthetically-generated images are getting increasingly popular. Diffusion models have advanced to the stage where even non-experts can generate photo-realistic images from a simple text prompt. They expand creative horizons but also open a Pandora's box of potential disinformation risks. In this context, the present corpus of synthetic image detection techniques, primarily focusing on older generative models like Generative Adversarial Networks, finds itself ill-equipped to deal with this emerging trend.
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 2024 in Korea.
The IEEE Signal Processing Society (SPS) announces the 2024 Class of Distinguished Lecturers and Distinguished Industry Speakers for the term of 1 January 2024 to 31 December 2025. The IEEE SPS Distinguished Lecturer (DL) Program provides a means for Chapters to have access to well-known educators and authors in the fields of signal processing to lecture at Chapter meetings.
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.
Date: 2-5 December 2024
Location: Rome, Italy
Date: 14 December 2023
Chapter: Tunisia Chapter
Chapter Chair: Maha Charfeddine
Title: From R2-D2 to Samantha: Artificial Emotional Intelligence Evolved
Date: 9-12 December 2024
Location: Macau, China
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