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Multi-Agent Consensus Subject to Communication and Privacy Constraints
We consider a multi-agent consensus problem in the presence of adversarial agents. The adversaries are able to listen to the inter-agent communications and try to estimate the state of the agents. The agents have a limited bit-r ... Read More >
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Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-res ...
The recent outbreak of COVID-19 has motivated researchers to contribute in the area of medical imaging using artificial intelligence and deep learning. Super-resolution (SR), in the past few years, has produced remarkable result ... Read More >
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QoE Optimization for Live Video Streaming in UAV-to-UAV Communications via Deep ...
A challenge for rescue teams when fighting against wildfire in remote areas is the lack of information, such as the size and images of fire areas. As such, live streaming from Unmanned Aerial Vehicles (UAVs), capturing videos of ... Read More >
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Classification of COVID-19 via Homology of CT-SCAN
In this worldwide spread of SARS-CoV-2 (COVID-19) infection, it is of utmost importance to detect the disease at an early stage especially in the hot spots of this epidemic. There are more than 110 Million infected cases on the ... Read More >
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False Data Injection Attack Against Power System Small-Signal Stability
Small-Signal Stability (SSS) is crucial for the control of power grids. However, False Data Injection (FDI) attacks against SSS can impact the grid stability, hence, the security of SSS needs to be studied. This paper proposes a ... Read More >
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Detection of Transformer Winding Axial Displacement by Kirchhoff and Delay and s ...
In this paper, a novel method for in detail detection of the winding axial displacement in power transformers based on UWB imaging is presented. In this method, the radar imaging process is implemented on the power transformer b ... Read More >
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Practical graph signal sampling with log-linear size scaling
Graph signal sampling is the problem of selecting a subset of representative graph vertices whose values can be used to interpolate missing values on the remaining graph vertices. Optimizing the choice of sampling set using conc ... Read More >
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Predicting Future Cognitive Decline with Hyperbolic Stochastic Coding
Hyperbolic geometry has been successfully applied in modeling brain cortical and subcortical surfaces with general topological structures. However such approaches, similar to other surface based brain morphology analysis methods ... Read More >
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Coherent Integration for Targets with Constant Cartesian Velocities Based on Acc ...
Long-time coherent integration (LTCI) is one of the most important techniques to improve radar detection performance of weak targets. However, for the targets moving with constant Cartesian velocities (CCV), the existing LTCI me ... Read More >
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Going beyond p-convolutions to learn grayscale morphological operators
Integrating mathematical morphology operations within deep neural networks has been subject to increasing attention lately. However, replacing standard convolution layers with erosions or dilations is particularly challenging be ... Read More >