Aggelos K. Katsaggelos

TL;DR: This study is focused on detection of AF rhythm using hand-held ECG monitoring devices, in addition to three other classes: normal or sinus rhythm, other rhythms, and too noisy to analyze.

TL;DR: The proposed unusual video event detection method is based on unsupervised clustering of object trajectories, which are modeled by hidden Markov models (HMM), and includes a dynamic hierarchical process incorporated in the trajectory clustering algorithm.

TL;DR: An algorithm for the identification of the blur and the restoration of a noisy blurred image that is exploited in computing the maximum likelihood estimates of the original image and the additive noise.

TL;DR: This paper introduces a new generator network optimized for the VSR problem, named VSRResNet, along with new discriminator architecture to properly guide V SRResNet during the GAN training, and introduces the PercepDist metric, which more accurately evaluates the perceptual quality of SR solutions obtained from neural networks, compared with the commonly used PSNR/SSIM metrics.

TL;DR: The problem of identifying the image and blur parameters and restoring a noisy blurred image is addressed and two algorithms for identification/restoration, based on two different choices of complete data, are derived and compared.