How deep learning extracts and learns leaf features for plant classification
- Submitting institution
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Kingston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11-51-1379
- Type
- D - Journal article
- DOI
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10.1016/j.patcog.2017.05.015
- Title of journal
- Pattern Recognition
- Article number
- -
- First page
- 1
- Volume
- 71
- Issue
- -
- ISSN
- 0031-3203
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
-
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- Citation count
- 142
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper reports the development of intelligent algorithms to identify and categorise plants, organs and plant related data. This is a new applied discipline of artificial intelligence and machine learning research, called computational botany, which aims at providing tools to botanists to classify plants. This research has helped securing an H2020 project in the field of natural intelligence. Its research prgram entails the development of deep learning methods applied to robot exploration in natural environments, towards the automatic classification of flora.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -