The use of machine-learning for multimedia forensics is gaining more and more consensus, especially due to the amazing possibilities offered by modern machine learning techniques. By exploiting deep learning tools, new approaches have been proposed whose performance remarkably exceed those achieved by state-of-the-art methods based on standard machine-learning and model-based techniques. 

Virtual reality (VR) holds tremendous potential to advance our society. It is expected to make impact on quality of life, energy conservation, and the economy, and reach a $162B market by 2022. 

The workshop is 22nd in the series, organized by the Multimedia Signal Processing Technical Committee of the IEEE Signal Processing Society, 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.

The IEEE Signal Processing Society would like to express our concern and support for the members of our global community and all affected by the current COVID-19 pandemic. We appreciate your continued patience and support as we work together to navigate these unforeseen and uncertain circumstances. We hope that you, your families, and your communities are safe!

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.

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.

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 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.