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Pound's work centers on the use of [[machine learning]], [[deep learning]], and bioimage analysis for the purpose of plant [[Phenotype|phenotyping]].<ref name="pw_security" /><ref>{{cite journal |last1=Pound |first1=Michael |last2=Atkinson |first2=Jonathan |last3=Wells |first3=Darren |last4=Pridmore |first4=Tony |last5=French |first5=Andrew |title=Deep Learning for Multi-task Plant Phenotyping |journal=IEEE Xplore |date=October 2017 |url=http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w29/Pound_Deep_Learning_for_ICCV_2017_paper.pdf |accessdate=3 September 2018}}</ref> 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.<ref>{{cite journal |last1=Atanbori |first1=John |last2=Chen |first2=Feng |last3=French |first3=Andrew |last4=Pridmore |first4=Tony |title=Towards Low-Cost Image-based Plant Phenotyping using Reduced-Parameter CNN. |pages=1 |url=https://www.plant-phenotyping.org/lw_resource/datapool/systemfiles/elements/files/42aa0773-949c-11e8-8a88-dead53a91d31/current/document/0023.pdf |accessdate=3 September 2018}}</ref> |
Pound's work centers on the use of [[machine learning]], [[deep learning]], and bioimage analysis for the purpose of plant [[Phenotype|phenotyping]].<ref name="pw_security" /><ref>{{cite journal |last1=Pound |first1=Michael |last2=Atkinson |first2=Jonathan |last3=Wells |first3=Darren |last4=Pridmore |first4=Tony |last5=French |first5=Andrew |title=Deep Learning for Multi-task Plant Phenotyping |journal=IEEE Xplore |date=October 2017 |url=http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w29/Pound_Deep_Learning_for_ICCV_2017_paper.pdf |accessdate=3 September 2018}}</ref> 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.<ref>{{cite journal |last1=Atanbori |first1=John |last2=Chen |first2=Feng |last3=French |first3=Andrew |last4=Pridmore |first4=Tony |title=Towards Low-Cost Image-based Plant Phenotyping using Reduced-Parameter CNN. |pages=1 |url=https://www.plant-phenotyping.org/lw_resource/datapool/systemfiles/elements/files/42aa0773-949c-11e8-8a88-dead53a91d31/current/document/0023.pdf |accessdate=3 September 2018}}</ref> |
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The image analysis tool RootNav was developed by a research team led by Pound. The tool uses image analysis to identify complex root system architectures.<ref name="RootNav_Primary">{{cite journal |last1=Pound |first1=Michael |last2=French |first2=Andrew |last3=Atkinson |first3=Jonathan |last4=Wells |first4=Darren |last5=Malcolm |first5=Bennet |last6=Pridmore |first6=Tony |title=RootNav: Navigating images of complex root architectures |journal=Plant Physiology |date=1 January 2013 |pages=113.221531 }}</ref> 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.<ref name="phenotyping_and_beyond">{{cite journal |last1=Granier |first1=Christine |last2=Vile |first2=Denis |title=Phenotyping and beyond: modelling the relationships between traits |journal=Current Opinion in Plant Biology |date=2014 |pages=96–102 |url=https://s3.amazonaws.com/academia.edu.documents/45201387/Phenotyping_and_beyond_modelling_the_rel20160429-6415-dqjsj0.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1536001420&Signature=qkgxBFbBLaUsSt2huK0VsHKqR0c%3D&response-content-disposition=inline%3B%20filename%3DPhenotyping_and_beyond_modelling_the_rel.pdf |accessdate=3 September 2018}}{{dead link}}</ref> |
The image analysis tool RootNav was developed by a research team led by Pound. The tool uses image analysis to identify complex root system architectures.<ref name="RootNav_Primary">{{cite journal |last1=Pound |first1=Michael |last2=French |first2=Andrew |last3=Atkinson |first3=Jonathan |last4=Wells |first4=Darren |last5=Malcolm |first5=Bennet |last6=Pridmore |first6=Tony |title=RootNav: Navigating images of complex root architectures |journal=Plant Physiology |date=1 January 2013 |pages=113.221531 }}</ref> 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.<ref name="phenotyping_and_beyond">{{cite journal |last1=Granier |first1=Christine |last2=Vile |first2=Denis |title=Phenotyping and beyond: modelling the relationships between traits |journal=Current Opinion in Plant Biology |date=2014 |pages=96–102 |url=https://s3.amazonaws.com/academia.edu.documents/45201387/Phenotyping_and_beyond_modelling_the_rel20160429-6415-dqjsj0.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1536001420&Signature=qkgxBFbBLaUsSt2huK0VsHKqR0c%3D&response-content-disposition=inline%3B%20filename%3DPhenotyping_and_beyond_modelling_the_rel.pdf |accessdate=3 September 2018}}{{dead link|date=March 2019}}</ref> |
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==Media appearances== |
==Media appearances== |
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Revision as of 01:59, 25 March 2019
Michael Pound | |
|---|---|
 Michael in 2018 | |
| Other names | Mike Pound |
| Occupation(s) | Professor, Lecturer, Researcher |
| 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 professor and researcher at the University of Nottingham.[1] He is known for his work in the areas of bioimage analysis, computer vision, image recognition, and computer security and for his appearances on the video series Computerphile.
Academic Work
Pound's work centers on the use of machine learning, deep learning, and bioimage analysis for the purpose of plant phenotyping.[2][3] 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.[4]
The image analysis tool RootNav was developed by a research team led by Pound. The tool uses image analysis to identify complex root system architectures.[5] 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.[6]
Media appearances
Pound has made numerous appearances on Brady Haran's video series Computerphile. During these appearances, Pound has discussed numerous aspects of his work including password cracking, brute forcing, kernel convolution and image analysis.[7][2]
See also
References
- ^ "Michael Pound". University of Nottingham. Retrieved 2 September 2018.
- ^ a b Keeper Security. "Keeper Q&A: What You Can Learn From Michael Pound's Scary Password-Cracking Video". Keeper. Keeper Security, Inc. Retrieved 2 September 2018.
- ^ Pound, Michael; Atkinson, Jonathan; Wells, Darren; Pridmore, Tony; French, Andrew (October 2017). "Deep Learning for Multi-task Plant Phenotyping" (PDF). IEEE Xplore. Retrieved 3 September 2018.
- ^ Atanbori, John; Chen, Feng; French, Andrew; Pridmore, Tony. "Towards Low-Cost Image-based Plant Phenotyping using Reduced-Parameter CNN" (PDF): 1. Retrieved 3 September 2018.
{{cite journal}}: Cite journal requires|journal=(help) - ^ Granier, Christine; Vile, Denis (2014). "Phenotyping and beyond: modelling the relationships between traits" (PDF). Current Opinion in Plant Biology: 96–102. Retrieved 3 September 2018.[dead link]
- ^ Muller, Tiffany. "Listen to an Expert Image Analyst Easily Explain the Science Behind Photo Filters". DIY Photography. Retrieved 2 September 2018.
External links
| Authority control databases: Academics |
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