62 citations · 107 across the 7 of their papers we have counts for
5 papers · 1 filter
Advances in Diffusion Models for Image Data Augmentation: A Review of Methods, Models, Evaluation Metrics and Future Research Directions
Panagiotis Alimisis, Ioannis Mademlis, Panagiotis Radoglou-Grammatikis +2
Image data augmentation constitutes a critical methodology in modern computer vision tasks, since it can facilitate towards enhancing the diversity and quality of training datasets…
Illicit object detection in X-ray images using Vision Transformers
Jorgen Cani, Ioannis Mademlis, Adamantia Anna Rebolledo Chrysochoou +1
Illicit object detection is a critical task performed at various high-security locations, including airports, train stations, subways, and ports. The continuous and tedious work of…
Self-supervised visual learning in the low-data regime: a comparative evaluation
Sotirios Konstantakos, Jorgen Cani, Ioannis Mademlis +4
Self-Supervised Learning (SSL) is a valuable and robust training methodology for contemporary Deep Neural Networks (DNNs), enabling unsupervised pretraining on a 'pretext task' tha…
Self-supervised visual learning for analyzing firearms trafficking activities on the Web
Sotirios Konstantakos, Despina Ioanna Chalkiadaki, Ioannis Mademlis +2
Automated visual firearms classification from RGB images is an important real-world task with applications in public space security, intelligence gathering and law enforcement inve…
Visual inspection for illicit items in X-ray images using Deep Learning
Ioannis Mademlis, Georgios Batsis, Adamantia Anna Rebolledo Chrysochoou +1
Automated detection of contraband items in X-ray images can significantly increase public safety, by enhancing the productivity and alleviating the mental load of security officers…