1 citations · 2 across the 4 of their papers we have counts for
7 papers
SAM2CLIP2SAM: Vision Language Model for Segmentation of 3D CT Scans for Covid-19 Detection
Dimitrios Kollias, Anastasios Arsenos, James Wingate +1
This paper presents a new approach for effective segmentation of images that can be integrated into any model and methodology; the paradigm that we choose is classification of medi…
Common Corruptions for Enhancing and Evaluating Robustness in Air-to-Air Visual Object Detection
Anastasios Arsenos, Vasileios Karampinis, Evangelos Petrongonas +4
The main barrier to achieving fully autonomous flights lies in autonomous aircraft navigation. Managing non-cooperative traffic presents the most important challenge in this proble…
Ensuring UAV Safety: A Vision-only and Real-time Framework for Collision Avoidance Through Object Detection, Tracking, and Distance Estimation
Vasileios Karampinis, Anastasios Arsenos, Orfeas Filippopoulos +5
In the last twenty years, unmanned aerial vehicles (UAVs) have garnered growing interest due to their expanding applications in both military and civilian domains. Detecting non-co…
Uncertainty-guided Contrastive Learning for Single Source Domain Generalisation
Anastasios Arsenos, Dimitrios Kollias, Evangelos Petrongonas +2
In the context of single domain generalisation, the objective is for models that have been exclusively trained on data from a single domain to demonstrate strong performance when c…
COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI System
Demetris Gerogiannis, Anastasios Arsenos, Dimitrios Kollias +2
Computer-aided diagnosis (CAD) systems stand out as potent aids for physicians in identifying the novel Coronavirus Disease 2019 (COVID-19) through medical imaging modalities. In t…
Domain adaptation, Explainability & Fairness in AI for Medical Image Analysis: Diagnosis of COVID-19 based on 3-D Chest CT-scans
Dimitrios Kollias, Anastasios Arsenos, Stefanos Kollias
The paper presents the DEF-AI-MIA COV19D Competition, which is organized in the framework of the 'Domain adaptation, Explainability, Fairness in AI for Medical Image Analysis (DEF-…