Identification of Plant Species using Supervised Machine Learning
Created by W.Langdon from
gp-bibliography.bib Revision:1.8120
- @Article{Tripathi:2018:IJCA,
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author = "Ankita Tripathi and Ravi Datta Sharma and
Shrawan Kumar Trivedi",
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title = "Identification of Plant Species using Supervised
Machine Learning",
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journal = "International Journal of Computer Applications",
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year = "2018",
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volume = "182",
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number = "13",
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pages = "6--12",
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month = sep,
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keywords = "genetic algorithms, genetic programming, Plant Species
Identification, Machine Learning Classifiers, Pattern
Recognition, Plant Species, Leaf image, Machine
learning, F-Value, FP rate, Training time",
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publisher = "Foundation of Computer Science (FCS), NY, USA",
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address = "New York, USA",
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ISSN = "0975-8887",
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URL = "http://www.ijcaonline.org/archives/volume182/number13/29920-2018917755",
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URL = "https://www.ijcaonline.org/archives/volume182/number13/tripathi-2018-ijca-917755.pdf",
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DOI = "doi:10.5120/ijca2018917755",
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size = "7 pages",
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abstract = "This research emphasizes on the plant species
recognition which is considered as an important area of
research in plant biotechnology. Artificial
intelligence and machine learning have a prominent
place in such research. In this study, a boosted
evolutionary plant species classifier has been
developed that works on ensemble of classifier methods.
This classifier identifies different species of plants
with the help of different texture and shape features
of leaf image. A publicly available plant image dataset
has been incorporated where features are extracted with
the help of image processing tools. The proposed
classifier is trained and tested with the help of these
features. Further, proposed classifier is compared with
other popular machine learning classifier viz.
Bayesian, Naive Bayes, SVM, J48, Random forest, Genetic
Programming. Proposed evolutionary classifier was found
to be good in terms of F-Value, FP rate and TP rate
whereas SVM was found to be under performing predictor
in this study. However, the training time of the
proposed classifier was high.",
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notes = "Also known as
\cite{10.5120/ijca2018917755}
www.ijcaonline.org
Amity institute of biotechnology, Amity University,
Gurgaon, India",
- }
Genetic Programming entries for
Ankita Tripathi
Ravi Datta Sharma
Shrawan Kumar Trivedi
Citations