collaborators

5 papers

q-bio.NC2019

Adversarial dictionary learning for a robust analysis and modelling of spontaneous neuronal activity

Eirini Troullinou, Grigorios Tsagkatakis, Ganna Palagina +3

The field of neuroscience is experiencing rapid growth in the complexity and quantity of the recorded neural activity allowing us unprecedented access to its dynamics in different…

cs.NE2019

Artificial neural networks in action for an automated cell-type classification of biological neural networks

Eirini Troullinou, Grigorios Tsagkatakis, Spyridon Chavlis +5

Identification of different neuronal cell types is critical for understanding their contribution to brain functions. Yet, automated and reliable classification of neurons remains a…

cs.DC2018

A Distributed Learning Architecture for Scientific Imaging Problems

A. Panousopoulou, S. Farrens, K. Fotiadou +4

Current trends in scientific imaging are challenged by the emerging need of integrating sophisticated machine learning with Big Data analytics platforms. This work proposes an in-m…

eess.IV2018

Convolutional Neural Networks for Video Quality Assessment

Michalis Giannopoulos, Grigorios Tsagkatakis, Saverio Blasi +5

Video Quality Assessment (VQA) is a very challenging task due to its highly subjective nature. Moreover, many factors influence VQA. Compression of video content, while necessary f…

astro-ph.IM2018

Convolutional Neural Networks for Spectroscopic Redshift Estimation on Euclid Data

Radamanthys Stivaktakis, Grigorios Tsagkatakis, Bruno Moraes +3

In this paper, we address the problem of spectroscopic redshift estimation in Astronomy. Due to the expansion of the Universe, galaxies recede from each other on average. This move…