4 citations · 4 across the 1 of their papers we have counts for
7 papers
Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT scans
Paschalis Bizopoulos, Nicholas Vretos, Petros Daras
Recently there has been an explosion in the use of Deep Learning (DL) methods for medical image segmentation. However the field's reliability is hindered by the lack of a common ba…
A Makefile for Developing Containerized LaTeX Technical Documents
Paschalis Bizopoulos
We propose a Makefile for developing containerized technical documents. The Makefile allows the author to execute the code that generates variables, tables and figures (re…
Sparsely Activated Networks: A new method for decomposing and compressing data
Paschalis Bizopoulos
Recent literature on unsupervised learning focused on designing structural priors with the aim of learning meaningful features, but without considering the description length of th…
Sparsely Activated Networks
Paschalis Bizopoulos, Dimitrios Koutsouris
Previous literature on unsupervised learning focused on designing structural priors with the aim of learning meaningful features. However, this was done without considering the des…
Signal2Image Modules in Deep Neural Networks for EEG Classification
Paschalis Bizopoulos, George I Lambrou, Dimitrios Koutsouris
Deep learning has revolutionized computer vision utilizing the increased availability of big data and the power of parallel computational units such as graphical processing units.…
Deep Learning in Cardiology
Paschalis Bizopoulos, Dimitrios Koutsouris
The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving compli…