IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society.

Nikos Sidiropoulos
Vice President-Membership and Chair, Chapters Review Committee

The IEEE Signal Processing Society Santa Clara Valley Chapter and the Vancouver Chapter have been selected as the recipients of the 2017 Chapter of the Year Award. This is the first year that two chapters have been designated with this honor!

IEEE is transitioning from wire payments and checks to direct wire transfers to your bank, also known as Automated Clearing House (ACH), or direct deposits, as its standard form of payment method for reimbursements to volunteers who work in the United States.  Direct deposit of payments is a more efficient, secure method of payment, and has been requested by many of our volunteers for several years.

Webinar Details: Wednesday, 13 December 2017 from 2:30pm - 3:30pm (New York time) 
Attendee Registration Link: Register for Webinar, by Dr. Nikos Sidiropoulos

CAMSAP 2017 Plenary - Tensors and Probability: An Intriguing Union: Abstract: We reveal an interesting link between tensors and multivariate statistics. The rank of a multivariate probability tensor can be interpreted as a nonlinear measure of statistical dependence of the associated random variables. 

Spy satellites and their commercial cousins orbit Earth like a swarm of space paparazzi, capturing tens of terabytes of images every day. The deluge of satellite imagery leaves U.S. intelligence agencies with the world’s biggest case of FOMO—“fear of missing out”—because human analysts can sift through only so many images to spot a new nuclear enrichment facility or missiles being trucked to different locations.

Neural networks are a set of biologically inspired algorithms that can be used to recognize patterns. Deep neural networks (DNNs) are neural networks that have much more layers in depth than traditional neural networks.

In the past decade, there has been a transformative and permanent revolution in computer vision cultivated by the reinvigorated adoption of deep learning for visual understanding tasks.