5 papers
Frugal Machine Learning for Energy-efficient, and Resource-aware Artificial Intelligence
John Violos, Konstantina-Christina Diamanti, Ioannis Kompatsiaris +1
Frugal Machine Learning (FML) refers to the practice of designing Machine Learning (ML) models that are efficient, cost-effective, and mindful of resource constraints. This field a…
Few-Shot Class-Incremental Learning For Efficient SAR Automatic Target Recognition
George Karantaidis, Athanasios Pantsios, Ioannis Kompatsiaris +1
Synthetic aperture radar automatic target recognition (SAR-ATR) systems have rapidly evolved to tackle incremental recognition challenges in operational settings. Data scarcity rem…
A Brief Review for Compression and Transfer Learning Techniques in DeepFake Detection
Andreas Karathanasis, John Violos, Ioannis Kompatsiaris +1
Training and deploying deepfake detection models on edge devices offers the advantage of maintaining data privacy and confidentiality by processing it close to its source. However,…
Reducing Inference Energy Consumption Using Dual Complementary CNNs
Michail Kinnas, John Violos, Ioannis Kompatsiaris +1
Energy efficiency of Convolutional Neural Networks (CNNs) has become an important area of research, with various strategies being developed to minimize the power consumption of the…
FaceX: Understanding Face Attribute Classifiers through Summary Model Explanations
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
EXplainable Artificial Intelligence (XAI) approaches are widely applied for identifying fairness issues in Artificial Intelligence (AI) systems. However, in the context of facial a…