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10 years of news and resources for members of the IEEE Signal Processing Society

Initiatives & Trends

Georgia Tech professor David Citrin is revealing the secrets of 17th century artists thanks to 21st century signal processing. Using modern high-speed scanners and the advanced signal processing techniques, researchers at the Georgia Institute of Technology are peering through layers of pigment to see how painters prepared their canvasses, applied undercoats, and built up layer upon layer of paint to produce their masterpieces.
 

How can we use modern signal processing and artificial intelligence to enhance medical devices such as hearing aids? A new startup called Mythic in a Redwood City, California, is trying to revive analog computing for artificial intelligence.

Boston Dynamics, a leading developer of advanced dynamic robots, recently released a video showing that their humanoid robot Atlas can do backflips now.

Alterations in brain development during infancy may precede the behavioral manifestation of developmental disorders. Infants at increased risk for autism are also at increased risk for other developmental disorders, including, quite commonly, language disorders. In this paper, the authors assess the extent to which electroencephalographic (EEG) signal differences in infants at high versus low familial risk for autism are present by 3 months of age, and elucidate the functional significance of EEG power at 3 months in predicting later development.

Machine learning and new signal/image processing techniques are changing our lives at a rapid pace. However, would you think that your vending machine may actually have facial recognition algorithms to offer you a drink? That's new and interesting, but not so distant future.

For more details, please read https://venturebeat.com/2017/10/21/vending-machines-are-getting-smarter-with-machine-learning-and-facial-recognition/

For our November 2017 issue, we cover recent patents granted in the area of image and audio inpainting

Google recently announced a new labeled dataset of human actions taking place in videos, named Atomic Visual Actions (AVA). It densely annotates 80 atomic visual actions in 57.6k movie clips with actions localized in space and time, resulting in 210k action labels with multiple labels per human occurring frequently. Compared with existing datasets, AVA possesses the following main characteristics:

For our October 2017 issue, we cover recent patents granted in the area of compressed sensing.
Patent no. 9,755,714 proposes methods and systems for performing compressed time domain joint channel estimation in a multi-user MIMO LTE wireless network include receiving training signals from a plurality of users, estimating a maximum delay spread for the received data according to a coherence bandwidth...

Researchers from University of California, Berkeley have developed an AI that turns a horse video into a zebra video.

The following is from the abstract of the authors' paper, titled "Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks".

For our September 2017 issue, we cover recent patents granted in the area of infrared imaging and signal processing.

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