| Interpretability of deep learning models: A survey of results S Chakraborty, R Tomsett, R Raghavendra, D Harborne, M Alzantot, ... 2017 IEEE smartworld, ubiquitous intelligence & computing, advanced …, 2017 | 599 | 2017 |
| Stakeholders in explainable AI A Preece, D Harborne, D Braines, R Tomsett, S Chakraborty arXiv preprint arXiv:1810.00184, 2018 | 282 | 2018 |
| Interpretable to whom? A role-based model for analyzing interpretable machine learning systems R Tomsett, D Braines, D Harborne, A Preece, S Chakraborty arXiv preprint arXiv:1806.07552, 2018 | 234 | 2018 |
| Sanity checks for saliency metrics R Tomsett, D Harborne, S Chakraborty, P Gurram, A Preece Proceedings of the AAAI conference on artificial intelligence 34 (04), 6021-6029, 2020 | 196 | 2020 |
| A Systematic Method to Understand Requirements for Explainable AI (XAI) Systems M Hall, D Harborne, R Tomsett, V Galetic, S Quintana-Amate, A Nottle, ... Proceedings of the IJCAI Workshop on eXplainable Artificial Intelligence …, 2019 | 73 | 2019 |
| Developing the sensitivity of LIME for better machine learning explanation E Lee, D Braines, M Stiffler, A Hudler, D Harborne Artificial intelligence and machine learning for multi-domain operations …, 2019 | 65 | 2019 |
| Interpretable to whom R Tomsett, D Braines, D Harborne, A Preece, S Chakraborty A role-based model for analyzing interpretable machine learning systems, 2018 | 42 | 2018 |
| Efficient orchestration of node-red iot workflows using a vector symbolic architecture C Simpkin, I Taylor, D Harborne, G Bent, A Preece, RK Ganti Future Generation Computer Systems 111, 117-131, 2020 | 25 | 2020 |
| 2017 IEEE smartworld, ubiquitous intelligence & computing, advanced & trusted computed, scalable computing & communications, cloud & big data computing, Internet of people and … S Chakraborty, R Tomsett, R Raghavendra, D Harborne, M Alzantot, ... IEEE,, 2017 | 21 | 2017 |
| A deep convolutional network for traffic congestion classification C Willis, D Harborne, R Tomsett, M Alzantot Proceedings of the NATO IST-158/RSM-010 Specialists’ Meeting on Content …, 2017 | 19 | 2017 |
| Dynamic distributed orchestration of node-red iot workflows using a vector symbolic architecture C Simpkin, I Taylor, D Harborne, G Bent, A Preece, RK Ganti 2018 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS), 52-63, 2018 | 18 | 2018 |
| Developing an objective indicator of fatigue: An alternative mobile version of the Psychomotor Vigilance Task (m-PVT) MS Evans, D Harborne, AP Smith International Symposium on Human Mental Workload: Models and Applications, 49-71, 2018 | 18 | 2018 |
| Integrating learning and reasoning services for explainable information fusion D Harborne, C Willis, R Tomsett, AD Preece ICPRAI 2018 - International Conference on Pattern Recognition and Artificial …, 2018 | 16 | 2018 |
| Conversational homes: a uniform natural language approach for collaboration among humans and devices D Braines, N O'leary, A Thomas, D Harborne, AD Preece, WM Webberley International Journal on Advances in Intelligent Systems 10 (3/4), 223-237, 2017 | 16 | 2017 |
| Distributed opportunistic sensing and fusion for traffic congestion detection A Nottle, D Harborne, D Braines, M Alzantot, S Quintana-Amate, ... 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced …, 2017 | 12 | 2017 |
| An analysis of reliability using lime with deep learning models M Stiffler, A Hudler, E Lee, D Braines, D Mott, D Harborne Annual Fall Meeting of the Distributed Analytics and Information Science …, 2018 | 9 | 2018 |
| Interpretability of deep learning models: a survey of results. in 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing … S Chakraborty, R Tomsett, R Raghavendra, D Harborne, M Alzantot, ... IEEE.[Google Scholar], 2017 | 7 | 2017 |
| Stakeholders in Explainable AI, ArXiv A Preece, D Harborne, D Braines, R Tomsett, S Chakraborty arXiv preprint arXiv:1810.00184, 2018 | 6 | 2018 |
| Stakeholders in explainable AI. arXiv 2018 A Preece, D Harborne, D Braines, R Tomsett, S Chakraborty arXiv preprint arXiv:1810.00184, 0 | 6 | |
| Multimodal explanations for ai-based multisensor fusion D Braines, A Preece, D Harborne NATO SET-262 RSM on artificial intelligence for military multisensor fusion …, 2018 | 5 | 2018 |
Alun PreeceCardiff University - Security Crime and Intelligence Innovation InstituteEmail confirmado em cardiff.ac.uk
