Artificial intelligence (AI) and machine learning (ML) as an application of AI, has today become an inevitable part of major industries such as healthcare, financial trending, and transportation. Future urgent need to intelligently utilize wireless resources to meet the need of ever-increasing diversity in services and user behavior, has actuated the wireless communication industry to deploy AI and ML techniques.

In this era of stress-filled life styles and cut-throat competitions, cardiovascular diseases and heart abnormalities are becoming common in the people of early age groups.

The IEEE Signal Processing Society (SPS) invites nominations for the position of Editor-in-Chief for the following journal: IEEE Signal Processing Magazine for a 3-year term starting 1 January 2021.

The Signal Processing Society (SPS) has 13 Technical Committees and 2 Special Interest Groups (SIGs) 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.

Dr. Pascale Fung is a Professor at the Department of Electronic & Computer Engineering and the Department of Computer Science & Engineering at The Hong Kong University of Science & Technology (HKUST).

The workshop is 22nd in the series, organized by the Multimedia Signal Processing Technical Committee of the IEEE Signal Processing Society (SPS), with the aim to bring together researchers and practitioners from academia and industry, passionate about multimedia signal processing, to share their knowledge, exchange ideas, explore future research directions and network.

Though the effects of the COVID-19 pandemic presented the world with unforeseen challenges, the IEEE Signal Processing Society is committed to exploring new ways to innovate, providing our global community with even more opportunities to connect, collaborate, and discover the latest research and breakthroughs from signal processing professionals throughout the world. Even if we weren’t initially seeing you in-person this year, we hope you’ll mark your calendar to and join us for these pioneering virtual events!

In the past decade, deep learning methods have achieved unprecedented performance on a broad range of problems in various fields from computer vision to speech recognition. So far research has mainly focused on developing deep learning methods for Euclidean-structured data.