18 citations · 71 across the 16 of their papers we have counts for
11 papers · 1 filter
Sanity Checks for Saliency Metrics
Richard Tomsett, Dan Harborne, Supriyo Chakraborty +2
Saliency maps are a popular approach to creating post-hoc explanations of image classifier outputs. These methods produce estimates of the relevance of each pixel to the classifica…
AAAI FSS-19: Artificial Intelligence in Government and Public Sector Proceedings
Frank Stein, Alun Preece
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA, November 7-8, 2019
Explainable AI for Intelligence Augmentation in Multi-Domain Operations
Alun Preece, Dave Braines, Federico Cerutti +1
Central to the concept of multi-domain operations (MDO) is the utilization of an intelligence, surveillance, and reconnaissance (ISR) network consisting of overlapping systems of r…
BMVC 2019: Workshop on Interpretable and Explainable Machine Vision
Alun Preece
Proceedings of the BMVC 2019 Workshop on Interpretable and Explainable Machine Vision, Cardiff, UK, September 12, 2019.
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…