In accordance with the Bylaws of the IEEE Signal Processing Society, I am writing to solicit nominations for the Awards Board and the Nominations and Appointments (N&A) Committee. This year, the Society will be filling TWO positions on the N&A Committee for the term 2023-2024 and TWO positions on the Awards Board for the term 2023-2025. 

Recently, deep convolutional neural network (CNNs) have been widely used in Single Image Super-Resolution (SISR) and have obtained great success. However, most of the existing methods are limited to local receptive field and equal treatment of different types of information; 

Intelligent reflecting surface (IRS) has recently emerged as a promising paradigm for future wireless communications. Owing to its remarkable capability in reshaping the propagation environment, IRS has a great potential to boost spectral efficiency, mitigate interference, and enhance physical security. 

This webinar presents ‘Tapestry’, a single-round pooled testing method with application to COVID-19 testing using quantitative Reverse Transcription Polymerase Chain Reaction (RT-PCR) that can result in shorter testing time and conservation of reagents and testing kits, at clinically acceptable false positive or false negative rates.

The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.

The IEEE annual election begins on 15 August and ends on 3 October.  All ballots must be received by 12:00 p.m. EDT/16:00 UTC.  The IEEE Signal Processing Society is committed to ensuring that its members are prepared with sufficient information about the candidates in order to make their best-informed decision. 

Audio pattern recognition is an important research topic in the machine learning area, and includes several tasks such as audio tagging, acoustic scene classification, music classification, speech emotion classification, and sound event detection. Recently, neural networks have been applied to tackle audio pattern recognition problems. 

This SPS webinar will introduce a novel data-driven cooperative localization and location data processing framework, called FedLoc, in line with the emerging machine learning and optimization techniques.

The Audio Engineering Society (AES), the IEEE Consumer Technology Society (CTSoc), and the IEEE Signal Processing Society (SPS) cordially invite you to a first-of-a-kind joint event discussing the state of the art perspectives in this rapidly evolving field.

The intent of this webinar is to demonstrate the optimality of splines for the resolution of inverse problems in imaging and the design of deep neural networks. To that end, I first present a representer theorem that states that the extremal points of a broad class of linear inverse problems with a generalized total-variation constraint are adaptive splines whose type is linked to the underlying regularization operator.