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Signal Processing Over Sensor Networks
Design of signal processing methods that are decentralized, robust against transmission failure, and smart enough to make use of network topology for (near) real-time data processing. Analysis of speech enhancement by distributed beamforming, speaker tracking and information fusion from camera networks. Development of methods suitable for smart grids, social networks and the Internet of things.
Very large scale sensor networks for well-being
Deep Learning via Distributed Optimisation
Training of large-scale deep neural networks to address the challenges associated with complexity and nonlinearity. Development of new frameworks to train neural networks via distributed optimisation over graphic models. Development of training processes that are efficient, transparent and understandable. The research outcomes aim to provide simple and efficient algorithms for deep learning-based industrial activities.
Signal Processing Over Sensor Networks
Design of signal processing methods that are decentralized, robust against transmission failure, and smart enough to make use of network topology for (near) real-time data processing. Analysis of speech enhancement by distributed beamforming, speaker tracking and information fusion from camera networks. Development of methods suitable for smart grids, social networks and the Internet of things.
Very large scale sensor networks for well-being
Deep Learning via Distributed Optimisation
Training of large-scale deep neural networks to address the challenges associated with complexity and nonlinearity. Development of new frameworks to train neural networks via distributed optimisation over graphic models. Development of training processes that are efficient, transparent and understandable. The research outcomes aim to provide simple and efficient algorithms for deep learning-based industrial activities.
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论文共 82 篇作者统计合作学者相似作者
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CVPR 2023 (2023): 1421-1429
IEEE Transactions on Signal and Information Processing over Networks (2023): 242-257
ICDIPpp.91:1-91:7, (2023)
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arXiv (Cornell University) (2023)
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