3 citations · 3 across the 5 of their papers we have counts for
6 papers
DF-CBM: Region-Aware Concept Bottleneck Models for Deepfake Detection
Georgios Tsoumplekas, Vazgken Vanian, Alexandros Doumanoglou +4
Deepfake detection methods have become increasingly effective yet most provide limited insight into the evidence behind their predictions. However, in forensic settings users also…
Training-Free Multi-Concept LoRA Composition with Prompt-Aware Weighting
Georgios Tsoumplekas, Stella Bounareli, Vasileios Argyriou
Low-Rank Adaptation (LoRA) successfully enables personalization in text-to-image generation by adapting pre-trained diffusion models to specific visual concepts and styles. However…
A Closer Look at Data Augmentation Strategies for Finetuning-Based Low/Few-Shot Object Detection
Vladislav Li, Georgios Tsoumplekas, Ilias Siniosoglou +4
Current methods for low- and few-shot object detection have primarily focused on enhancing model performance for detecting objects. One common approach to achieve this is by combin…
Enhancing Performance for Highly Imbalanced Medical Data via Data Regularization in a Federated Learning Setting
Georgios Tsoumplekas, Ilias Siniosoglou, Vasileios Argyriou +2
The increased availability of medical data has significantly impacted healthcare by enabling the application of machine / deep learning approaches in various instances. However, me…
Evaluating the Energy Efficiency of Few-Shot Learning for Object Detection in Industrial Settings
Georgios Tsoumplekas, Vladislav Li, Ilias Siniosoglou +5
In the ever-evolving era of Artificial Intelligence (AI), model performance has constituted a key metric driving innovation, leading to an exponential growth in model size and comp…
A Complete Survey on Contemporary Methods, Emerging Paradigms and Hybrid Approaches for Few-Shot Learning
Georgios Tsoumplekas, Vladislav Li, Panagiotis Sarigiannidis +1
Despite the widespread success of deep learning, its intense requirements for vast amounts of data and extensive training make it impractical for various real-world applications wh…