Biography:Michael Pound
Michael Pound | |
|---|---|
 Michael in 2018 | |
| Other names | Mike Pound |
| Occupation | Lecturer, Researcher, Media Personality |
| Years active | Present |
| Academic work | |
| Discipline | Computer Science |
| Sub-discipline | Bioimage analysis, computer vision, image recognition, computer security |
| Institutions | University of Nottingham |
Michael P. Pound is a researcher at the University of Nottingham.[1] He is known for his work in the areas of bioimage analysis, computer vision, image recognition, computer security, and for his appearances on the video series Computerphile.[2]
Career
Pound's work focuses on the use of machine learning, deep learning, and bioimage analysis for the purpose of plant phenotyping.[3][4] His work on the identification of root and leaf tips through image-based phenotyping has been recognized as important in the field of bioimage analysis.[5]
The image analysis tool RootNav[6] was developed by a research team led by Pound. The tool uses image analysis to identify complex root system architectures.[7] It has been made available to the scientific community and has been used by other researchers in the field to facilitate batch processing of high numbers of images in various studies of plant phenotyping.[8]
Media appearances
Pound has made numerous appearances on Brady Haran's video series Computerphile. During these appearances, Pound has discussed aspects of his work including password cracking, brute forcing, kernel convolution and image analysis.[9][3]
References
- ↑ "Michael Pound". https://www.nottingham.ac.uk/biosciences/people/michael.pound. Retrieved 2 September 2018.
- ↑ "Computerphile". https://www.youtube.com/user/Computerphile.
- ↑ 3.0 3.1 Keeper Security (2016-11-07). "Keeper Q&A: What You Can Learn From Michael Pound's Scary Password-Cracking Video". Keeper Security, Inc. https://keepersecurity.com/blog/2016/11/07/keeper-qa-what-you-can-learn-from-michael-pounds-scary-password-cracking-video/. Retrieved 2 September 2018.
- ↑ Pound, Michael P.; Atkinson, Jonathan A.; Wells, Darren M.; Pridmore, Tony P.; French, Andrew P. (2017). "Deep Learning for Multi-task Plant Phenotyping". 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). pp. 2055–2063. doi:10.1109/ICCVW.2017.241. ISBN 978-1-5386-1034-3. http://eprints.nottingham.ac.uk/47610/1/Pound_Deep_Learning_for_ICCV_2017_paper.pdf.
- ↑ Atanbori, John; Chen, Feng; French, Andrew; Pridmore, Tony. Towards Low-Cost Image-based Plant Phenotyping using Reduced-Parameter CNN.. pp. 1. https://www.plant-phenotyping.org/lw_resource/datapool/systemfiles/elements/files/42aa0773-949c-11e8-8a88-dead53a91d31/current/document/0023.pdf. Retrieved 3 September 2018.
- ↑ Yasrab, Robail (2020-09-22), robail-yasrab/RootNav-2.0, https://github.com/robail-yasrab/RootNav-2.0, retrieved 2020-10-26
- ↑ Granier, Christine; Vile, Denis (2014). "Phenotyping and beyond: modelling the relationships between traits". Current Opinion in Plant Biology 18: 96–102. doi:10.1016/j.pbi.2014.02.009. PMID 24637194.[|permanent dead link|dead link}}]
- ↑ Muller, Tiffany (2015-10-03). "Listen to an Expert Image Analyst Easily Explain the Science Behind Photo Filters". https://www.diyphotography.net/listen-to-an-expert-image-analyst-easily-explain-the-science-behind-photo-filters/. Retrieved 2 September 2018.
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