Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Subject interpretability
Showing results 1 to 4 of 4
| Issue Date | Title | Author(s) |
|---|---|---|
| 12-Dec-2021 | Accuracy and Explainability in Artificial Intelligence: Unpacking the Terms | McGrath, K |
| 6-Dec-2021 | A Biologically Interpretable Two-Stage Deep Neural Network (BIT-DNN) for Vegetation Recognition from Hyperspectral Imagery | Shi, Y; Han, L; Huang, W; Chang, S; Dong, Y; Dancey, D; Han, L |
| 3-Aug-2026 | Interpreting networks via semantic probes with correction and counterfactuals | Cheng, Keyang; Wan, Hao; He, Ligang; Li, Maozhen; Tian, Qing |
| 31-Mar-2022 | Vision-Language Transformer for Interpretable Pathology Visual Question Answering | Naseem, U; Khushi, M; Kim, J |