most citedBenchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches

1 citations · 1 across the 9 of their papers we have counts for

collaborators

9 papers

cs.HC2025

Enhancing Manufacturing Training Through VR Simulations

Vladislav Li, Ilias Siniosoglou, Panagiotis Sarigiannidis +1

In contemporary training for industrial manufacturing, reconciling theoretical knowledge with practical experience continues to be a significant difficulty. As companies transition…

cs.CV2024

Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis

Vladislav Li, Ilias Siniosoglou, Thomai Karamitsou +6

Autonomous Vehicles (AVs) use natural images and videos as input to understand the real world by overlaying and inferring digital elements, facilitating proactive detection in an e…

cs.LG2024

Applied Federated Model Personalisation in the Industrial Domain: A Comparative Study

Ilias Siniosoglou, Vasileios Argyriou, George Fragulis +4

The time-consuming nature of training and deploying complicated Machine and Deep Learning (DL) models for a variety of applications continues to pose significant challenges in the…

cs.CV2024

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…

cs.NI2024

CloudCap (C2app) : A Cloud-Based Platform for Packet Analysis On The Edge

Kyriazis Kokkinos, Ioannis Polymenidis, Ilias Siniosoglou +2

Data exchange through mobile devices is rapidly increasing due to the high information demands of today's applications. The need for monitoring the exchanged traffic becomes import…

cs.LG2024

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…

cs.CL2024

Evaluating the Efficacy of AI Techniques in Textual Anonymization: A Comparative Study

Dimitris Asimopoulos, Ilias Siniosoglou, Vasileios Argyriou +5

In the digital era, with escalating privacy concerns, it's imperative to devise robust strategies that protect private data while maintaining the intrinsic value of textual informa…

cs.CL2024★ 1 cited

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…

cs.LG2024

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…