IEEE Signal Processing Magazine

You are here

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

IEEE Signal Processing Magazine

I am excited to start my service as the IEEE Signal Processing Society (SPS) president. I should note that I am the first SPS president directly elected by the SPS membership, due to the SPS Board of Governors (BOG) urging a stronger member voice in elections. This is a big honor for me and I would like to express my thanks to SPS members for their trust. I write this article to introduce myself, acknowledge key volunteers and staff for their service, outline the activities I will lead over the next two years, and invite your comments and suggestions.
The November 2021 IEEE Technical Activities Board meeting presentations articulated several warning signs and promising calls to action. A new, radical proposal to change the way IEEE elevates its Members to Fellow status may finally address the inclusion and equity issues that we discuss but have yet to address. The proposal is still in its infancy and was drafted by a committee chaired by our very own Jose Moura. It recognizes and documents what many of us have known anecdotally: the success rate of Fellow nominations coming from industry, government, and regions outside North America and Europe is abysmally low, despite the quality of the nominees.
Multiscale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. Scientific computed tomography (SCT) instruments are one of the most popular choices for 3D nondestructive characterization of materials at length scales ranging from the angstrom scale to the micron scale. These instruments typically have a source of radiation (such as electrons, X-rays, or neutrons) that interacts with the sample to be studied and a detector assembly to capture the result of this interaction (see Figure 1 ).
The Markov random field (MRF) is one of the most widely used models in image processing, constituting a prior model for addressing problems such as image segmentation, object detection, and reconstruction. What is not often appreciated is that the MRF owes its origin to the physics of solids, making it an ideal prior model for processing microscopic observations of materials. While both fields know of their respective interpretations of the MRF, each knows very little about the other’s version of it. Hence, both fields have “blind spots,” where some concepts readily appreciated by one field are completely obscured from the other. 
In an age when signal processing lies at the core of so many different technologies, nothing is more important than its contribution to health care. From improved cardiac patient support to enhanced magnetic resonance imaging (MRI) and advanced diagnostics, signal processing is helping physicians work more safely, efficiently, and accurately. Here is a look at three important research projects that are using signal processing to assist both patients and health-care providers.
With the year coming to a close, I couldn’t help but reflect on our experiences in 2020 and 2021. I began my term as president of the IEEE Signal Processing Society (SPS) roughly 65 days before we were told to work from home due to the COVID-19 pandemic. As I write this column 18 months later, I find myself, like many of you, still largely working remotely.
Given the increasing prevalence of facial analysis technology, the problem of bias in the tools is now becoming an even greater source of concern. Several studies have highlighted the pervasiveness of such discrimination, and many have sought to address the problem by proposing solutions to mitigate it. Despite this effort, to date, understanding, investigating, and mitigating bias for facial affect analysis remain an understudied problem.
Researchers in an almost endless number of fields are embracing artificial intelligence (AI) and machine learning (ML) to develop tools and systems that can predict and adapt to a wide range of changing situations, optimize system performance, and intelligently filter signals. In areas as diverse as firefighter protection, solar power optimization, and exoplanet discovery, researchers are turning to AI, ML, and signal processing to help them achieve breakthroughs that were unimaginable only a few years ago.
Recent advances in the field of machine learning have shown great potential for the automatic recognition of apparent human emotions. In the era of Internet of Things and big-data processing, where voice-based systems are well established, opportunities to leverage cutting-edge technologies to develop personalized and human-centered services are genuinely real, with a growing demand in many areas such as education, health, well-being, and entertainment. 
Affective computing is computing that relates to, arises from, or deliberately influences emotion or other affective phenomena. Human emotion and affect in general are fundamental to human experience, influencing cognition, perception, and everyday tasks such as learning and communication, but are also fundamental to human health and well-being. 

Pages

SPS on Twitter

  • Attention students! The 2022 5-Minute Video Clip Contest begins soon! This year's topic, "Graph Signal Processing a… https://t.co/QTMqxDaudy
  • Students, it's time to form your teams! The 2022 Signal Processing Cup competition is underway. This year's topic,… https://t.co/fVw7tA7zTG
  • The DEGAS Webinar Series continues this Thursday, 13 January when Peter Battaglia presents "Modeling Physical Struc… https://t.co/Kndvzl8BpE
  • The SPS Webinar Series continues on Wednesday, 26 January when Dr. Ba-Ngu Vo presents "Bayesian Multi-object Tracki… https://t.co/sKejcUeyys
  • Call for Speakers! The IEEE Women in Engineering International Leadership Conference () is seeking submissio… https://t.co/bSaRgMw2uD

SPS Videos


Signal Processing in Home Assistants

 


Multimedia Forensics


Careers in Signal Processing             

 


Under the Radar