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The Latest News, Articles, and Events in Signal Processing
Recently, deep neural network (DNN) based methods for low-dose CT have been investigated to achieve excellent performance in both image quality and computational speed. However, almost all methods using DNNs for low-dose CT require clean ground truth data with full radiation dose to train the DNNs. In this work, we attempt to train DNNs for low-dose CT reconstructions with reduced tube current by investigating unsupervised training of DNNs for denoising sensor measurements or sinograms without full-dose ground truth images.
Regularization by denoising (RED) is an image reconstruction framework that uses an image denoiser as a prior. Recent work has shown the state-of-the-art performance of RED with learned denoisers corresponding to pre-trained convolutional neural nets (CNNs). In this work, we propose to broaden the current denoiser-centric view of RED by considering priors corresponding to networks trained for more general artifact-removal.
One challenging aspect in face anti-spoofing (or presentation attack detection, PAD) refers to the difficulty of collecting enough and representative attack samples for an application-specific environment. In view of this, we tackle the problem of training a robust PAD model with limited data in an application-specific domain.
With the rapid progress in recent years, techniques that generate and manipulate multimedia content can now provide a very advanced level of realism. The boundary between real and synthetic media has become very thin. On the one hand, this opens the door to a series of exciting applications in different fields such as creative arts, advertising, film production, and video games. On the other hand, it poses enormous security threats. Software packages freely available on the web allow any individual, without special skills, to create very realistic fake images and videos.
Lecture Date: December 7, 2020 (Virtual Lecture)
Chapter: Beijing
Chapter Chair: Qiuqi Ruan
Topic: Binary optimizations in signal processing
Date: October 28, 2020
Time: 11:00 AM EDT (New York Time)
Title: Joint Optimization of Radio and Computational
Resources in Mobile Edge Computing
Registration | Full webinar details
In recent years, we have seen the emergence of new compute-intensive and delay-critical mobile applications, such as virtual/augmented reality, online gaming, ultra-high-definition video streaming and autonomous driving. Multi-access edge computing (MEC) has become a key technology in 5G networks to shift computational tasks from resource-limited mobile devices to nearby servers placed at the edge of the network.
White Paper Due: November 1, 2020
Publication Date: November 2021
CFP Document
White Paper Due: February 1, 2021
Publication Date: March 2022
CFP Document
Submission Deadline: February 19, 2021
Call for Proposals Document
This issue brings to you our interview with Dr. Ervin Sejdić, an Associate Professor at the Swanson School of Engineering, University of Pittsburgh, where he directs a research laboratory focused on engineering developments in medicine. His research has focused on creating computational biomarkers indicative of age- and disease-related changes in functional outcomes such as swallowing, gait, and handwriting.
IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form related to a particular TC field. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and selecting a particular TC.
The IEEE Signal Processing Society (SPS) would like to express our concern and support for the members of our global community and all affected by the current COVID-19 pandemic.
Each month, the Chapter Briefs Newsletter will feature an OU Analytics Tip that will be helpful to all who utilize the OU Analytics tool. This month's Tip features obtaining Membership Verification.
Each month, the Chapter Briefs Newsletter will feature an OU Analytics Tip that will be helpful to all who utilize the OU Analytics tool. This month's Tip features obtaining Membership Verification.
The IEEE Signal Processing Society (SPS) is launching PROGRESS - an initiative aiming to motivate and support women and under-represented minorities to pursue academic careers in signal processing. 2020 PROGRESS Workshop at ICIP 2020 (Virtual), 26-27 October 2020. Submission Deadline is 20 October 2020!
The IEEE Signal Processing Society (SPS) has extended the nomination period for the position of the Chair, Young Professionals Committee in order to allow for a more diverse slate of candidates.
Dr. Mari Ostendorf is an Endowed Professor of System Design Methodologies at the University of Washington in the Electrical & Computer Engineering Department, currently serving as Associate Vice Provost for Research. She is also an Adjunct Professor in Linguistics and in the Paul G. Allen School of Computer Science and Engineering.
Vimal Bhatia is a Professor in the Discipline of Electrical Engineering at the Indian Institute of Technology Indore, India. He is also an associated faculty with Centre for Advanced Electronics and Discipline of Astronomy, Astrophysics, and Space Engineering at IIT Indore.
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