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NEWS AND RESOURCES FOR MEMBERS OF THE IEEE SIGNAL PROCESSING SOCIETY

SPS Publications Alert: 2020 Tables of Contents Are Back!

You may have been wondering what happened to the list of tables of contents (TOCs) we were offering in the SPS Newsletter each month? Well, beginning in 2020, many of the SPS journals eliminated month-based issues and moved to volume-only publications; for these, there are no month-based TOCs. In order to address this, we worked to devise a method to collect a range of articles being posted to IEEEXplore® and assemble them into a separate, yet familiar, formatted TOC.

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ALASKA 2 Steganalysis Challenge is Open

The ALASKA 2 Steganalysis Challenge is now open!  The goal of the competition is to push the community towards image steganalysis, “into the wild” facing two main challenges: 1) The very high heterogeneity of image "sources", with widely different type of content, processing operations, sensor noises, etc. and 2) Designing machine learning method for detection with low false positive, ideally that could be guaranteed.  The entry deadline is 13 July 2020 at 11:59 PM (UTC). 

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Upcoming Webinar: "Distributed Localization and Tracking of Mobile Networks"

A new era of pervasive data generation is enabled by emerging sensing modalities and will pose new challenges to signal processing, data science, and robotics. For example, underwater robotic technology enables the development of advanced networks for underwater localization and mapping, and emerging aerial robotic technology enables the development of advanced networks for wide area localization and mapping. 

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Machine Learning Techniques for Image Forensics in Adversarial Setting

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. 

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