A new era of pervasive data generation is enabled by emerging sensing modalities and will pose new challenges to signal processing, data science, and robotics. For example, underwater robotic technology enables the development of advanced networks for underwater localization and mapping, and emerging aerial robotic technology enables the development of advanced networks for wide area localization and mapping. 

COVID-19 has disrupted the day-to-day activities of governments, corporates, and people across the globe. It is unfortunate that this virus has taken humanity to a stage where most of us spend time in isolation worrying about the future.

In the past decade, deep learning methods have achieved unprecedented performance on a broad range of problems in various fields from computer vision to speech recognition. So far research has mainly focused on developing deep learning methods for Euclidean-structured data.

With cloud storage services, users can remotely store their data to the cloud and realize the data sharing with others. Remote data integrity auditing is proposed to guarantee the integrity of the data stored in the cloud. In some common cloud storage systems, such as the electronic health records system, the cloud file might contain some sensitive information that should not be exposed to others when the cloud file is shared.

In this webinar, we'll introduce FemtoPixel: A framework for lensless imaging with compressive ultrafast sensing. The FemtoPixel framework provides single-pixel imaging capabilities that are up to 50X faster compared to traditional single-pixel camera techniques. 

This webinar, “Toward Efficient and Flexible CNN-based Denoising in Photography,” begins with the design of denoising CNN (DnCNN) model by incorporating residual learning and batch normalization. 

This webinar will address the problem of identifying the structure of an undirected graph from the observation of signals defined on its nodes. Fundamentally, the unknown graph encodes direct relationships between signal elements, which we aim to recover from observable indirect relationships generated by a diffusion process on the graph. 

IEEE is proud to introduce you to IEEE DataPort™, a valuable, easily accessible data platform that can significantly enhance your research efforts.  Upload and store standard or open-access datasets for free with the option to link your paper submission.™

Upcoming webinar, 29 January 2019 by Dr. Victor Elvira. In many problems of signal processing, the interest is in estimating unknown static variables given a set of observations. The hidden parameters and the available data are usually related through a specific model. 

King Li is dean and chief academic officer for Carle Illinois College of Medicine, created in partnership by the University of Illinois at Urbana-Champaign and the Carle Health System. When he went to medical school 40 years ago, he sometimes felt like he was trying to memorize the human body.