2 citations · 2 across the 1 of their papers we have counts for
4 papers
An Experimentation Platform for Explainable Coalition Situational Understanding
Katie Barrett-Powell, Jack Furby, Liam Hiley +8
We present an experimentation platform for coalition situational understanding research that highlights capabilities in explainable artificial intelligence/machine learning (AI/ML)…
Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models
Liam Hiley, Alun Preece, Yulia Hicks +3
A small subset of explainability techniques developed initially for image recognition models has recently been applied for interpretability of 3D Convolutional Neural Network model…
Explainable Deep Learning for Video Recognition Tasks: A Framework & Recommendations
Liam Hiley, Alun Preece, Yulia Hicks
The popularity of Deep Learning for real-world applications is ever-growing. With the introduction of high performance hardware, applications are no longer limited to image recogni…
Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity Recognition
Liam Hiley, Alun Preece, Yulia Hicks +2
Current techniques for explainable AI have been applied with some success to image processing. The recent rise of research in video processing has called for similar work n deconst…