Design and Implementation of a Low-Cost Intelligent Unmanned Surface Vehicle.

This article describes the design and construction journey of a self-developed unmanned surface vehicle (USV). In order to increase the accessibility and lower the barrier of entry we propose a low-cost (under EUR 1000) approach to the vessel construction with great adaptability and customizability. This design prioritizes minimal power consumption as a key objective.

White Matter Lesion Segmentation for Multiple Sclerosis Patients implementing deep learning.

The aim of this work is to address the problem of White Matter Lesion (WML) segmentation employing Magnetic Resonance Imaging (MRI) images from Multiple Sclerosis (MS) patients through the application of deep learning. A U-net based architecture containing a contrastive path and an expanding path prior to the final pixel-wise classification is implemented. The data are provided by the Ippokratio Radiology Center of Ioannina and include Fluid-Attenuated Inversion Recovery (FLAIR) MRI images from 30 patients in three phases, baseline and two follow ups.

Multiple Sclerosis Severity Estimation and Progression Prediction Based on Machine Learning Techniques.

The aim of the study is to address the Multiple Sclerosis (MS) severity estimation problem based on EDSS score and the prediction of the disease's progression with the application of Machine Learning (ML) approaches. Several ML techniques are implemented. The data are provided by the Neurology Clinic of the University Hospital of Ioannina and were collected in the framework of the ProMiSi project.