125 citations · 314 across the 30 of their papers we have counts for
8 papers · 1 filter
Solar Power driven EV Charging Optimization with Deep Reinforcement Learning
Stavros Sykiotis, Christoforos Menos-Aikateriniadis, Anastasios Doulamis +2
Power sector decarbonization plays a vital role in the upcoming energy transition towards a more sustainable future. Decentralized energy resources, such as Electric Vehicles (EV)…
Diabetic foot ulcers monitoring by employing super resolution and noise reduction deep learning techniques
Agapi Davradou, Eftychios Protopapadakis, Maria Kaselimi +2
Diabetic foot ulcers (DFUs) constitute a serious complication for people with diabetes. The care of DFU patients can be substantially improved through self-management, in order to…
Transferability limitations for Covid 3D Localization Using SARS-CoV-2 segmentation models in 4D CT images
Constantine Maganaris, Eftychios Protopapadakis, Nikolaos Bakalos +3
In this paper, we investigate the transferability limitations when using deep learning models, for semantic segmentation of pneumonia-infected areas in CT images. The proposed appr…
Automatic inspection of cultural monuments using deep and tensor-based learning on hyperspectral imagery
Ioannis N. Tzortzis, Ioannis Rallis, Konstantinos Makantasis +3
In Cultural Heritage, hyperspectral images are commonly used since they provide extended information regarding the optical properties of materials. Thus, the processing of such hig…
Towards trustworthy Energy Disaggregation: A review of challenges, methods and perspectives for Non-Intrusive Load Monitoring
Maria Kaselimi, Eftychios Protopapadakis, Athanasios Voulodimos +2
Non-intrusive load monitoring (NILM) is the task of disaggregating the total power consumption into its individual sub-components. Over the years, signal processing and machine lea…
TraCon: A novel dataset for real-time traffic cones detection using deep learning
Iason Katsamenis, Eleni Eirini Karolou, Agapi Davradou +4
Substantial progress has been made in the field of object detection in road scenes. However, it is mainly focused on vehicles and pedestrians. To this end, we investigate traffic c…