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Upcoming Webinar, 2 July 2021: Facial Expression Analysis with Attention Mechanism
Facial expressions are configurations of different muscle movements in the face. The local characters of muscle movements play an important role in distinguishing facial expressions by machines. In this webinar, the presenter will explore the local characters local characters of muscle movements by introducing the attention mechanism into two frameworks.
Graph Neural Networks
Filtering is the fundamental operation upon which the field of signal processing is built. Loosely speaking, filtering is a mapping between signals, typically used to extract useful information (output signal) from data (input signal). Arguably, the most popular type of filter is the linear and shift-invariant (i.e. independent of the starting point of the signal) filter, which can be computed efficiently by leveraging the convolution operation.
Series to Highlight Women in Signal Processing: Dr. Supavadee Aramvith
Dr. Supavadee Aramvith received her B.S. (first class honors) degree in Computer Science from Mahidol University, Bangkok, Thailand, in 1993. She received her M.S. and Ph.D. degrees in Electrical Engineering from the University of Washington, Seattle, USA, in 1996 and 2001, respectively.
Call for Nominations: Awards Board Chair and Fellow Evaluation Committee - Chair and Vice Chair Positions
The IEEE Signal Processing Society (SPS) invites nominations for the positions of Awards Board Chair and Fellow Evaluation Committee - Chair and Vice Chair. Nominations should be received no later than 30 July 2021.
Get Involved with Technical Committees by becoming a TC Affiliate
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.
Upcoming Webinar, 24 June 2021: Learning the MMSE Channel Estimator
This webinar will discuss the MMSE channel estimator for a simple SIMO system model, without knowledge of the required channel statistics. Although the derived MMSE estimator is computationally intractable in the general form, its structure can be used to motivate a neural network architecture with lower complexity.
Series to Highlight Women in Signal Processing: Monica Bugallo
Mónica F. Bugallo received her Ph.D. in computer science and engineering from University of A Coruña, Spain. She is a Professor of Electrical and Computer Engineering and the Vice Provost for Faculty Affairs, and Diversity, Equity and Inclusion at Stony Brook University, NY, USA. Bugallo is the current Chair of the IEEE SPS Signal Processing Theory and Methods Technical Committee, Senior Associate Editor of the IEEE Signal Processing Letters and Associate Editor of the IEEE Transactions on Signal Processing.
I-DeepLearn Workshop
I-DeepLearn aims to increase diversity in computer science and related field by inviting students from grades 10-12 to experience machine learning (Artificial Intelligence) and deep learning (AI processing) and their applications, specifically in the healthcare domain. In this one-week online workshop, students will learn about essential concepts in machine learning and deep learning through a dynamic mix of hands-on programming projects and interactive discussions.
Call for Proposals: Virtual Signal Processing Society Member Driven Initiatives Cycle 2
The Society offers funding under the Member Driven Initiatives program for events that encourage involvement by SPS membership, including local chapters, universities, industry members as well as individual members. Programs under the Member Driven Initiatives include the launched Forums and Regional Meetings, in addition to the existing Chapter Driven Initiatives.
108 Signal Processing Society Members Elevated to Senior Member!
The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 108 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.
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