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The Latest News, Articles, and Events in Signal Processing
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.
Human centric visual analysis tasks are essential to computer vision since humans are the key element for cameras to analyze. In this talk, I will mainly focus on 4 visual analysis tasks on human hand, gesture, pose, and action respectively.
The 2023 Multimedia Prize Paper Award Nomination period is now open! Eligibility: Any paper published (final publication, not Early Access) in the IEEE Transactions on Multimedia (T-MM) in 2020, 2021, or 2022.
The IEEE Transactions on Multimedia is now accepting nominations for the 2023 Multimedia Prize Paper Award. Nominations are due no later than 31 March 2023.
Date: 9 March 2023
Time: 9:00 AM ET (New York Time)
Presenter(s): Mr. Sayantan Dutta
Date: 13 February 2023
Time: 10:30 AM ET (New York Time)
Title: Human Centric Visual Analysis - Hand, Gesture, Pose, Action, and Beyond
Full webinar details
Date: 18 January 2023
Time: 3:00 PM (Paris Time)
Title: Robustness of Graph Neural Networks
Registration | Full webinar details
Graph neural networks (GNNs) have achieved impressive results in various graph learning tasks and they have found their way into many application domains. Despite their proliferation, our understanding of their robustness properties is still very limited.
Submission Deadline: 15 June 2023
Call for Proposals Document
Date: 15 February 2023
Time: 10:00 AM ET (New York Time)
Presenter(s): Mr. Wei Liu, Dr. Li Chen and Dr. Wenyi Zhang
Full webinar details
Date: 19 January 2023
Time: 1:00 PM ET (New York Time)
Full webinar details
Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data? As one such example, this work explores the low-light image enhancement problem, where in practice it is extremely challenging to simultaneously take a low-light and a normal-light photo of the same visual scene.
We are advertising for a two-year Post-Doc position at King’s College London to work with Prof. Osvaldo Simeone and Prof. Bipin Rajendran on AI and neuromorphic computing with applications to wireless communication systems. Of particular interest is the investigation, at fundamental theoretical and algorithmic levels, of digital twin platforms for the design and monitoring of next-generation cellular systems.
Recent advances in multimodal processing have led to promising solutions for speech-processing tasks. One example is automatic speech recognition (ASR), which is a key component in current speech-based systems.
First, I would like to wish you and your loved ones a nice new year filled with health and happiness. The last few years have been challenging for various reasons: the COVID-19 pandemic, climatic events, and the war in Ukraine, to name a few. It seems impossible to be able to stop the megalomania and madness of some human beings.
Recent years have witnessed a rapidly growing interest in next-generation imaging systems and their combination with machine learning. While model-based imaging schemes that incorporate physics-based forward models, noise models, and image priors laid the foundation in the emerging field of computational sensing and imaging, recent advances in machine learning, from large-scale optimization to building deep neural networks, are increasingly being applied in modern computational imaging.
The compressive sensing (CS) scheme exploits many fewer measurements than suggested by the Nyquist–Shannon sampling theorem to accurately reconstruct images, which has attracted considerable attention in the computational imaging community. While classic image CS schemes employ sparsity using analytical transforms or bases, the learning-based approaches have become increasingly popular in recent years. Such methods can effectively model the structure of image patches by optimizing their sparse representations or learning deep neural networks while preserving the known or modeled sensing process.
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May the year 2023 bring everyone closer to the fulfilment of their dreams. We have left behind a year marked with successes on multiple fronts, including health and technology as well as a year filled with proud people risking their lives for freedom. In particular, two big movements have captured our hearts: the fierce resistance of Ukranian people against the Russian invasion of their country, and the prodemocracy uprising in Iran with women in the lead.
Date: 31 October-3 November 2023
Location: Taipei, Taiwan
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