1 citations · 3 across the 6 of their papers we have counts for
6 papers
Connecting the Dots: Graph Neural Network Powered Ensemble and Classification of Medical Images
Aryan Singh, Pepijn Van de Ven, Ciarán Eising +1
Deep learning models have demonstrated remarkable results for various computer vision tasks, including the realm of medical imaging. However, their application in the medical domai…
Self-Supervised Online Camera Calibration for Automated Driving and Parking Applications
Ciarán Hogan, Ganesh Sistu, Ciarán Eising
Camera-based perception systems play a central role in modern autonomous vehicles. These camera based perception algorithms require an accurate calibration to map the real world di…
Hardware Accelerators in Autonomous Driving
Ken Power, Shailendra Deva, Ting Wang +2
Computing platforms in autonomous vehicles record large amounts of data from many sensors, process the data through machine learning models, and make decisions to ensure the vehicl…
Towards a performance analysis on pre-trained Visual Question Answering models for autonomous driving
Kaavya Rekanar, Ciarán Eising, Ganesh Sistu +1
This short paper presents a preliminary analysis of three popular Visual Question Answering (VQA) models, namely ViLBERT, ViLT, and LXMERT, in the context of answering questions re…
Compact & Capable: Harnessing Graph Neural Networks and Edge Convolution for Medical Image Classification
Aryan Singh, Pepijn Van de Ven, Ciarán Eising +1
Graph-based neural network models are gaining traction in the field of representation learning due to their ability to uncover latent topological relationships between entities tha…
Navigating Uncertainty: The Role of Short-Term Trajectory Prediction in Autonomous Vehicle Safety
Sushil Sharma, Ganesh Sistu, Lucie Yahiaoui +3
Autonomous vehicles require accurate and reliable short-term trajectory predictions for safe and efficient driving. While most commercial automated vehicles currently use state mac…