The MMSP 2018 team is inviting you to submit regular and special session papers to MMSP2018, the annual workshop organized by the Multimedia Signal Processing Technical Committee (MMSP TC) of the IEEE Signal Processing Society.

The IEEE Signal Processing Magazine page has a new look on the IEEE Signal Processing Society (SPS) website, and you can access it anywhere! The new page showcases the leading-edge content in a new design format.

How do home assistants understand your spoken words? Signal processing, of course!
In our newest video, Signal Processing in Home Assistants, we explore how signal processing engineers use signal processing and machine learning to make home assistant technology possible.

Signal processing is always at the heart of the technology that differentiates today’s generations from those of the past is reaffirmed once again by the special issue on Machine Learning for Cognition in Radio Communications and Radar in IEEE Journal of Selected Topics in Signal Processing, February 2018.

The November 2017 special issue of SPM on deep learning for visual understanding surveyed deep-learning solutions under reinforcement; weakly supervised and multimodal settings, investigated their robustness; and presented overviews of their applications in domain adaptation, hashing, semantic segmentation, metric learning, inverse problems in imaging, image-to-text generation, and picture-quality assessment.

Webinar Details: 15 March 2018 from 9:00am - 10:00am (EDT) 
Attendee Registration Link: Register for Webinar, by Dr. Sergios Theodoridis and Dr. Sotirios Chatzis
Topic: A Tour into Deep Learning: From Its Origins to Cutting Edge Research and Open Challenges

The IEEE Signal Processing Society is very excited to offer the next webinar in our new series featuring “technical and technological innovations and their applications in signal processing” from top researchers and thought leaders in academia and industry. 

For our March 2018 issue, we cover recent patents granted in the area of image segmentation
In patent no 9,886,647 systems, devices, and methods are presented for segmenting an image of a video stream with a client device by accessing a set of images within a video stream, identifying an object of interest within one or more images of the set of images, and detecting a region of interest within the one or more images. 

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.

Sensor networks deployed in high-latency environments such as underwater acoustic and satellite channels find critical applications in disaster prevention and tactical surveillance. The sensors in these networks have limited energy reserves.