activity
20202026
most citedDeep learning based black spot identification on Greek road networks

13 citations · 17 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

AmalthAI: An Open-Source Computer Vision Platform for Cultural Heritage

Christos Chatzisavvas, Stelios Alvanos, Efstratios Politis +13

Computer vision (CV) and machine learning (ML) offer new tools for cultural heritage (CH) artifact analysis, but the CV/ML pipeline remains largely inaccessible to CH domain expert…

eess.AS2024

Locality enhanced dynamic biasing and sampling strategies for contextual ASR

Md Asif Jalal, Pablo Peso Parada, George Pavlidis +8

Automatic Speech Recognition (ASR) still face challenges when recognizing time-variant rare-phrases. Contextual biasing (CB) modules bias ASR model towards such contextually-releva…

cs.CV2023

Towards Explainability in Monocular Depth Estimation

Vasileios Arampatzakis, George Pavlidis, Kyriakos Pantoglou +2

The estimation of depth in two-dimensional images has long been a challenging and extensively studied subject in computer vision. Recently, significant progress has been made with…

cs.LG2023★ 13 cited

Deep learning based black spot identification on Greek road networks

Ioannis Karamanlis, Alexandros Kokkalis, Vassilios Profillidis +4

Black spot identification, a spatiotemporal phenomenon, involves analyzing the geographical location and time-based occurrence of road accidents. Typically, this analysis examines…

cs.LG2023★ 4 cited

Defect detection using weakly supervised learning

Vasileios Sevetlidis, George Pavlidis, Vasiliki Balaska +3

In many real-world scenarios, obtaining large amounts of labeled data can be a daunting task. Weakly supervised learning techniques have gained significant attention in recent year…

cs.CV2020

Deep learning approaches in food recognition

Chairi Kiourt, George Pavlidis, Stella Markantonatou

Automatic image-based food recognition is a particularly challenging task. Traditional image analysis approaches have achieved low classification accuracy in the past, whereas deep…