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The Latest News, Articles, and Events in Signal Processing

Prof. Christian Jutten received Ph.D. (1981) and Doctor es Sciences (1987) degrees from Grenoble Institute of Technology, France. He was Associate Professor (1982-1989), Professor (1989-2019), and in September 2019, became Professor Emeritus at University Grenoble Alpes. 

Elisa Konofagou is the Robert and Margaret Hariri Professor of Biomedical Engineering and Professor Radiology as well as Director of the Ultrasound and Elasticity Imaging Laboratory at Columbia. Her main interests are in the development of novel elasticity imaging techniques and therapeutic ultrasound methods.

Do you know someone who has made notable contributions to signal processing or service to the IEEE Signal Processing Society? Now is your chance to recognize them by nominating them for an SPS award!

May 13-15, 2022
Registration Deadline: N/A
Location: Kerala, India

Lecture Date: May 6, 2022 -- Virtual Lecture
Chapter: Madras Chapter
Chapter Chair: N. Venkateswaran
Topic: Spectral Methods for Data Science

Massachusetts Institute of Technology

The MIT Laboratory for Information and Decision Systems (LIDS) at the MIT Institute for Data, Systems, and Society (IDSS) and the MIT Schwarzman College of Computing is seeking applicants for a Postdoctoral Scholar to perform independent research in the broad areas of machine learning and intelligent systems, mentored by Prof. Navid Azizan (azizan.mit.edu).

IEEE Transactions on Information Forensics and Security

Near-InfraRed and VISual (NIR-VIS) face matching, as one of the most representative tasks in Heterogeneous Face Recognition (HFR), aims at retrieving a face image across different domains. With the development of deep learning and the growing demand for intelligent surveillance, it has aroused more and more research attention in the computer vision community.

IEEE Transactions on Information Forensics and Security

With the wide use of smartphones, more private data are collected and saved in the smartphones. This raises higher requirements for secure and effective user authentication scheme. Continuous authentication leverages behavioral biometrics as identity information and shows promising characteristics for user verification in a continuous and passive means.

IEEE Transactions on Computational Imaging

Hyperspectral imaging (HSI) has become an invaluable imaging tool for many applications in astrophysics or Earth observation. Unfortunately, direct observation of hyperspectral images is impossible since the actual measurements are 2-D and suffer from strong spatial and spectral degradations, especially in the infrared.

IEEE Transactions on Audio, Speech and Language Processing

Deep neural networks (DNNs) represent the mainstream methodology for supervised speech enhancement, primarily due to their capability to model complex functions using hierarchical representations. However, a recent study revealed that DNNs trained on a single corpus fail to generalize to untrained corpora, especially in low signal-to-noise ratio (SNR) conditions.

IEEE Transactions on Audio, Speech and Language Processing

In many real-world settings, machine learning models need to identify user inputs that are out-of-domain (OOD) so as to avoid performing wrong actions. This work focuses on a challenging case of OOD detection, where no labels for in-domain data are accessible (e.g., no intent labels for the intent classification task).

IEEE Signal Processing Letters

Recent years have witnessed remarkable success of Graph Fourier Transform (GFT) in point cloud attribute compression. Existing researches mainly utilize geometry distance to define graph structure for coding attribute (e.g., color), which may distribute high weights to the edges connecting points across texture boundaries. 

IEEE Open Journal of Signal Processing

Beside the minimizationof the prediction error, two of the most desirable properties of a regression scheme are stability and interpretability . Driven by these principles, we propose continuous-domain formulations for one-dimensional regression problems. In our first approach, we use the Lipschitz constant as a regularizer, which results in an implicit tuning of the overall robustness of the learned mapping.

IEEE Journal of Selected Topics in Signal Processing
Network slicing to support multi-tenancy plays a key role in improving the performance of 5G and beyond networks. In this paper, we study dynamically slicing network resources in the backhaul and Radio Access Network (RAN) prior to user demand observations across multiple tenants, where each tenant owns and operates several slices to provide different services to users.

MIMO communication remains an important technology for wireless communication systems. In this tutorial, we revisit classical signal processing models for MIMO wireless communications. We consider how those models may be updated as MIMO systems go to higher carrier frequencies, broader bandwidths and new kinds of array architectures.

In this talk, we investigate the model-driven deep learning for multiple input-multiple output (MIMO) detection. In particular, the MIMO detector is specially designed by unfolding an iterative algorithm and adding some trainable parameters. 

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