| IEEE Signal Processing Society

18 Signal Processing Society Members Elevated to Senior Member

The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 18 of its members to the grade of IEEE Senior Member. These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest. Senior Member is the only membership grade that is eligible to be nominated for IEEE Fellow. The new Senior Members of the IEEE Signal Processing Society are:

Signal Processing Conferences

Please refer to the following webpage for the latest updates on upcoming conferences in Signal Processing. Listing of all conferences

Activity Update from the MLSP Technical Committee

The Machine Learning for Signal Processing Technical Committee (MLSP TC) is involved with activities that facilitate the use of machine learning techniques for signal processing problems through advances in both the theory and practice of machine learning.

Recent Patents in Signal Processing (October 2016) – Radar imaging

For our October 2016 issue, we cover recent patents dealing with radar imaging.

Activity Update from the IFS-TC

The Information Forensics and Security Technical Committee (IFS TC) reports on the IEEE Signal Processing Cup 2016, Multimedia Forensics in the news.the WIFS 2016 to be held in Abu Dhabi and more.

What Should We Learn From... Ethics and Autonomous Systems: Perils and Promises

Learn about Ethics and Autonomous Systems in Ronald C. Arkin's article in Proceedings of the IEEE.

Yang, Fan. (University of Maryland, College Park), “Leveraging Multiple Features for Image Retrieval and Matching” (2016)

Yang, Fan. (University of Maryland, College Park), “Leveraging Multiple Features for Image Retrieval and Matching” (2016) Advisor: Davis, Larry S. The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task.

Simpkins, Jonathan (University of Notre Dame), “Modeling, approximation, and estimation of spatially-varying blur in photographic systems” (2016)

Simpkins, Jonathan (University of Notre Dame), “Modeling, approximation, and estimation of spatially-varying blur in photographic systems” (2016) Advisor: Stevenson, Robert L. Several image restoration and analysis approaches, such as deconvolution, superresolution, and depth-from-defocus, require an accurate representation of the photographic blurring process.

Video of the Month: Interact With Pokemon Go Monsters Using Interactive Dynamic Video

Researchers from MIT have developed "Interactive Dynamic Video", a technology that allows the background to interact with Pokemon and virtual forces. It analyzes video clips to find vibration patterns at different frequencies, which represent distinct ways that an object can move.

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