Search Results for author:
Found 10 papers, 2 papers with code
Domain-informed graph neural networks: a quantum chemistry case study
We explore different strategies to integrate prior domain knowledge into the design of a deep neural network (DNN).
Detecting Humans in RGB-D Data with CNNs
We address the problem of people detection in RGB-D data where we leverage depth information to develop a region-of-interest (ROI) selection method that provides proposals to two color and depth CNNs.
A DNN Framework for Learning Lagrangian Drift With Uncertainty
Reconstructions of Lagrangian drift, for example for objects lost at sea, are often uncertain due to unresolved physical phenomena within the data.
Adaptive Neighbourhoods for the Discovery of Adversarial Examples
Deep Neural Networks (DNNs) have often supplied state-of-the-art results in pattern recognition tasks.
Integrating linguistic knowledge into DNNs: Application to online grooming detection
Online grooming (OG) of children is a pervasive issue in an increasingly interconnected world.
Learnable Gabor modulated complex-valued networks for orientation robustness
Robustness to transformation is desirable in many computer vision tasks, given that input data often exhibits pose variance.
VI-Net: View-Invariant Quality of Human Movement Assessment
We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data.
VIMPNN: A physics informed neural network for estimating potential energies of out-of-equilibrium systems
Our method is extensively evaluated on a augmented version of the QM9 dataset that includes unstable molecules, as well as a new dataset of infinite- and finite-size crystals, and is compared with the Message Passing Neural Network (MPNN).
Calorie Counter: RGB-Depth Visual Estimation of Energy Expenditure at Home
We present a new framework for vision-based estimation of calorific expenditure from RGB-D data - the first that is validated on physical gas exchange measurements and applied to daily living scenarios.
Multiple Human Tracking in RGB-D Data: A Survey
Finally, we present a brief comparative evaluation of the performance of those works that have applied their methods to these datasets.
