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) |
|---|---|---|
| 2018 | Deep learning in classifying depth of anesthesia (DoA) | AlMeer, MH; Abbod, MF |
| 2019 | Detecting defects in PCB using deep learning via convolution neural networks | Adibhatla, VA; Shieh, JS; Abbod, MF; Chih, HC; Hsu, CC; Cheng, J |
| 2020 | Applications of machine learning to machine fault diagnosis: A review and roadmap | Lei, Y; Yang, B; Jiang, X; Jia, F; Li, N; Nandi, AK |
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