1 citations · 2 across the 5 of their papers we have counts for
5 papers
Enhancing Object Detection with Privileged Information: A Model-Agnostic Teacher-Student Approach
Matthias Bartolo, Dylan Seychell, Gabriel Hili +4
This paper investigates the integration of the Learning Using Privileged Information (LUPI) paradigm in object detection to exploit fine-grained, descriptive information available…
Learning Using Privileged Information for Litter Detection
Matthias Bartolo, Konstantinos Makantasis, Dylan Seychell
As litter pollution continues to rise globally, developing automated tools capable of detecting litter effectively remains a significant challenge. This study presents a novel appr…
Correlation of Object Detection Performance with Visual Saliency and Depth Estimation
Matthias Bartolo, Dylan Seychell
As object detection techniques continue to evolve, understanding their relationships with complementary visual tasks becomes crucial for optimising model architectures and computat…
Deep Learning for Speaker Identification: Architectural Insights from AB-1 Corpus Analysis and Performance Evaluation
Matthias Bartolo
In the fields of security systems, forensic investigations, and personalized services, the importance of speech as a fundamental human input outweighs text-based interactions. This…
Integrating Saliency Ranking and Reinforcement Learning for Enhanced Object Detection
Matthias Bartolo, Dylan Seychell, Josef Bajada
With the ever-growing variety of object detection approaches, this study explores a series of experiments that combine reinforcement learning (RL)-based visual attention methods wi…