activity
20202026
most citedDetecting Parkinsonian Tremor from IMU Data Collected In-The-Wild using Deep Multiple-Instance Learning

78 citations · 85 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2026

Deep Learning for Biopsy-Free Subtyping of Basal Cell Carcinoma from Dermatoscopic Images

Alexandros Papadopoulos, Chrysa Episkopou, Ioannis Sarafis +2

Basal Cell Carcinoma (BCC) is the most common type of skin cancer, accounting for nearly 80% of skin cancer di- agnoses. Its optimal clinical management is guided by the distinct h…

cs.CV2025

Weakly Supervised Food Image Segmentation using Vision Transformers and Segment Anything Model

Ioannis Sarafis, Alexandros Papadopoulos, Anastasios Delopoulos

In this paper, we propose a weakly supervised semantic segmentation approach for food images which takes advantage of the zero-shot capabilities and promptability of the Segment An…

cs.CV2023

Food Image Classification and Segmentation with Attention-based Multiple Instance Learning

Valasia Vlachopoulou, Ioannis Sarafis, Alexandros Papadopoulos

The demand for accurate food quantification has increased in the recent years, driven by the needs of applications in dietary monitoring. At the same time, computer vision approach…

cs.LG20237 cited

Leveraging Unlabelled Data in Multiple-Instance Learning Problems for Improved Detection of Parkinsonian Tremor in Free-Living Conditions

Alexandros Papadopoulos, Anastasios Delopoulos

Data-driven approaches for remote detection of Parkinson's Disease and its motor symptoms have proliferated in recent years, owing to the potential clinical benefits of early diagn…

cs.ET2022

Dynamic Programmable Wireless Environment with UAV-mounted Static Metasurfaces

Prodromos-Vasileios Mekikis, Dimitrios Tyrovolas, Sotiris Tegos +8

Reconfigurable intelligent surfaces (RISs) are artificial planar structures able to offer a unique way of manipulating propagated wireless signals. Commonly composed of a number of…

cs.ET2022

An Open Platform for Simulating the Physical Layer of 6G Communication Systems with Multiple Intelligent Surfaces

Alexandros Papadopoulos, Antonios Lalas, Konstantinos Votis +4

Reconfigurable Intelligent Surfaces (RIS) constitute a promising technology that could fulfill the extreme performance and capacity needs of the upcoming 6G wireless networks, by o…