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.
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| Issue Date | Title | Author(s) |
|---|---|---|
| 2013 | Detecting anomalies in multivariate time series from automotive systems | Theissler, Andreas |
| 2020 | Broken Power Strand Detection with Aerial Images: A Machine Learning based Approach | Pan, Y; Liu, F; Yang, J; Zhang, W; Li, Y; Lai, CS; Wu, X; Lai, LL; Hong, B |
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