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November 26-29, 2019
Registration Deadline: November 1, 2019
Location: Verona, Italy
Website
P2IRC Computer Science Research Positions
Posted: August 2, 2019
Lecture Date: August 26, 2019
Chapter: Hamilton
Chapter Chair: Jun Chen
Topic: A Joint Attention Decoding and Adaptive
Beamforming Optimization Approach for the Cocktail Party Problem
Applications are invited for a postdoctoral position in the area of machine learning and data analytics for human performance understanding and prediction, a collaborative effort at Tufts University among the Department of Electrical and Computer Engineering, Department of Computer Science, the Center for Applied Brain and Cognitive Sciences (CABCS) at Tufts University and the U.S.
The Signal Processing and Knowledge Technology research groups at the Universität Hamburg are hiring a research associate (PhD candidate) for the project "Ego-Noise Reduction for Interactive Robots".
This paper presents a time-frequency masking based online multi-channel speech enhancement approach that uses a convolutional recurrent neural network to estimate the mask. The magnitude and phase components of the short-time Fourier transform coefficients for multiple time frames are provided as an input such that the network is able to discriminate between the directional speech...
The seven papers in this special issue cover various far-field speech processing techniques including speech enhancement, separation and recognition, and their integration. In most of the methods, multichannel speech processing is an essential component to achieve state-of-the-art performance.
In this paper, we propose a coding tree unit (CTU)-level rate control scheme from the perspective of SSIM-based rate-distortion optimization to improve the coding efficiency. First, we establish the SSIM-based rate-distortion model based on the divisive normalization scheme, which characterizes the relationship between the local visual quality and the coding bits.
With the rapid popularization of mobile intelligent terminals, mobile video and cloud services applications are widely used in people's lives. However, the resource-constrained characteristic of the terminals and the enormous amount of video information make the efficient terminal-to-cloud data upload a challenge.
Multimedia streams consume a significant chunk of the consumer Internet traffic exchanged and will continue to do so due to the ever-increasing connection among people, businesses, and industries. To cope with the deviation of the Internet's intended use, unreliable underlying infrastructure, and best effort protocols while leveraging existing technologies...
Online Applications only: http://emea3.mrted.ly/28n6x
The University of Luxembourg is a multilingual, international research university.
Online Application Only:http://emea3.mrted.ly/28f97
The University of Luxembourg is a multilingual, international research university.
The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD holders for conducting research in design and optimization methods for performance enhancement of next generation radar networks
In many communication channels, secrecy constraints usually incur a penalty in capacity, as well as generalized degrees-of-freedom (GDoF). In this paper, we show an interesting observation that adding a helper can totally remove the penalty in sum GDoF for a two-user symmetric Gaussian interference channel.
The Internet of Things (IoT) is increasingly empowering people with an interconnected world of physical objects ranging from smart buildings to portable smart devices, such as wearables. With recent advances in mobile sensing, wearables have become a rich collection of portable sensors and are able to provide various types of services...
The use of mobile phones in public places opens up the possibilities of remote side channel attacks on these devices. We present a video-based side channel attack to decipher passwords on mobile devices. Our method uses short video clips ranging from 5 to 10 s each, which can be taken unobtrusively from a distance and do not require the keyboard or the screen of the phone to be visible.
The discrete Mumford-Shah formalism has been introduced for the image denoising problem, allowing to capture both smooth behavior inside an object and sharp transitions on the boundary. In this letter, we propose first to extend this formalism to graphs and to the problem of mixing matrix estimation.
Zero-shot learning (ZSL) has enjoyed great popularity in recent years due to its ability to recognize novel objects, where semantic information is exploited to build up relations among different categories. Traditional ZSL approaches usually focus on learning more robust visual-semantic embeddings among seen classes and directly apply them to the unseen classes without considering whether they are suitable.