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SPS Newsletter Article

The Signal Processing Society is pleased to announce the 5-Minute Video Clip Contest (5-MICC) at ICASSP in Singapore May 22-27, 2022. The topic chosen this year is graph signal processing (GSP) and its applications. Graph signals arise in various applications, such as sensor networks, power systems, social networks, and biological studies. 

The talk conveys a vision of Machine Learning Security based on Information Forensics and Security. In a nutshell, the IFS community protects three cardinal values (confidentiality, integrity, and property) of informative
content, be it a transmitted signal (physical layer), an image (watermarking), or some text (fake news detection), for instance.

Sound field estimation using a microphone array is a fundamental problem in acoustic signal processing, which has a wide variety of applications, such as visualization/auralization of an acoustic field, spatial audio reproduction using a loudspeaker array or headphones, and active noise cancellation in a spatial region.

As a popular signal modeling technique, sparse representation (SR) has achieved great success in image fusion during the last decade. However, due to the patch-based manner adopted in standard SR models, most existing SR-based image fusion methods suffer from two drawbacks, namely, limited ability in detail preservation and high sensitivity to mis-registration, while these two issues are of great concern in image fusion. 

Many problems encountered in sensing and imaging can be formulated as estimating a low-rank object from incomplete, and possibly corrupted, linear measurements; prominent examples include matrix completion and tensor completion. 

The 2022 International Conference on Acoustics, Speech, & Signal Processing (ICASSP) invites proposals for its Signal Processing Grand Challenges (SPGC) program. ICASSP is the IEEE Signal Processing Society’s flagship conference targeting signal processing and its applications.

Adaptive (i.e., data-driven) methods have become very popular these last decades. Among the existing techniques, the empirical mode decomposition has proven to be very efficient in extracting accurate time-frequency information from non-stationary signals.

I received my Ph.D. degree from University of Southern California (USC), Los Angeles, CA. Currently I am an Associate Professor and Associate Head of Information Systems Technology and Design (ISTD), Singapore University of Technology and Design (SUTD). I have been an active researcher in the field of Image Processing and Computer Vision. My research has resulted in 14 U.S. patents granted with several pending. Two of my inventions have been licensed to companies. 

The DSLW team is inviting you to submit regular papers to the 2022 IEEE Data Science & Learning Workshop (DSLW 2022), a workshop organized by the IEEE Signal Processing Society (supported by the SPS Data Science Initiative). The workshop aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science, learning theory and applications.

The DSLW team is inviting you to submit regular papers to the 2022 IEEE Data Science & Learning Workshop (DSLW 2022), a workshop organized by the IEEE Signal Processing Society (supported by the SPS Data Science Initiative). The workshop aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science, learning theory and applications.

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