2 citations · 3 across the 8 of their papers we have counts for
8 papers
Emotion Recognition and Generation: A Comprehensive Review of Face, Speech, and Text Modalities
Rebecca Mobbs, Dimitrios Makris, Vasileios Argyriou
Emotion recognition and generation have emerged as crucial topics in Artificial Intelligence research, playing a significant role in enhancing human-computer interaction within hea…
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…
Benchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches
Dimitris Asimopoulos, Ilias Siniosoglou, Vasileios Argyriou +6
In the realm of data privacy, the ability to effectively anonymise text is paramount. With the proliferation of deep learning and, in particular, transformer architectures, there i…
Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly Detection
Demetris Lappas, Vasileios Argyriou, Dimitrios Makris
We introduce Dynamic Distinction Learning (DDL) for Video Anomaly Detection, a novel video anomaly detection methodology that combines pseudo-anomalies, dynamic anomaly weighting,…
An AI-Assisted Skincare Routine Recommendation System in XR
Gowravi Malalur Rajegowda, Yannis Spyridis, Barbara Villarini +1
In recent years, there has been an increasing interest in the use of artificial intelligence (AI) and extended reality (XR) in the beauty industry. In this paper, we present an AI-…
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…