The Multimedia Signal Processing Technical Committee (MMSP-TC) of the IEEE Signal Processing Society, which is the organizer of the MMSP workshop, invites proposals for the 2020 workshop edition. 

Image, Video, and Multidimensional Signal Processing Technical Committee (IVMSP TC) promotes and guides the advancement of the field of image, video, and multidimensional signal processing.

IEEE MGA is excited to announce the expansion of our online petition form to include submissions for Sections, Subsections and Status Changes! Online petition submissions are already available for Student Branches, Student Branch Chapters, Student Branch Affinity Groups, Technical Chapters and Affinity Groups. 

The IEEE Signal Processing Society continues to track emerging technical areas. As a result, the Society has decided to create two new SPS Technical Interest Profile (TIP) Code categories in the fields of Data Science and Autonomous Systems to keep pace with the expanding technical disciplines.

For our September 2018 issue, we cover recent patents granted in the area of Simultaneous localization and mapping (SLAM), both from algorithm and hardware development sides.

In today’s big and messy data age, there is a lot of data generated everywhere around us. Examples include texts, tweets, network traffic, changing Facebook connections, or video surveillance feeds coming in from one or multiple cameras. Dimension reduction and noise/outlier removal are usually important preprocessing steps before any high-dimensional (big) data set can be used for inference.

When deciding on a career path, you’re likely to have different considerations in mind. You want to have a skillset for which there is a wide demand in growing industries. You also need to be certain your expertise will remain relevant in the technologically uncertain years to come, when AI and automation will change many of our jobs as we know it.

For our August 2018 issue, we cover recent patents granted in the area of Lidar based scene analysis. Patent no. 10,031,231 presents an object-detection system suitable for an automated vehicle which includes a lidar and a controller. The lidar is used to detect a point-cloud that is organized into a plurality of scan-lines.