Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/249482
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DC FieldValueLanguage
dc.coverage.spatialPlant Leaf Classification
dc.date.accessioned2019-07-08T04:50:45Z-
dc.date.available2019-07-08T04:50:45Z-
dc.identifier.urihttp://hdl.handle.net/10603/249482-
dc.description.abstractPlants play an important role in both human life and other lives that exist on the earth Plants play the most critical impact in the cycle of nature Plant recognition is very demanding in biology and agriculture as new plant discovery and the computerization of the administration of plant species turns out to be more famous newlineAutomatic plant classification systems are essential for a wide range of applications including environmental protection plant resource survey as well as for education Apart from using the whole plant the automation of plant identification can be performed using various parts of a plant anatomy like stem flower petal seed and leaf This research focuses on the automation of plant identification through leaf recognition Automated identification of plant species using leaf images is a worthwhile goal because of the current combination of rapidly decreasing biodiversity and the shortage of suitably qualified taxonomists This is particularly important in geographic locations which currently have a huge number of species and the largest number of species restricted to that geographic area newline newline
dc.format.extentxxiii, 209p.
dc.languageEnglish
dc.relationp.194-207
dc.rightsuniversity
dc.titlePlant leaf classification using hybrid low level features with enhanced feature selection algorithm
dc.title.alternative
dc.creator.researcherVijay Lakshmi B
dc.subject.keywordHybrid Low Level Features
dc.subject.keywordLife Sciences,Plant and Animal Science,Plant Sciences
dc.subject.keywordPlant Leaf Classification
dc.subject.keywordPlants
dc.description.note
dc.contributor.guideMohan V
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Science and Humanities
dc.date.registeredn.d.
dc.date.completed2017
dc.date.awarded31/07/2017
dc.format.dimensions21 cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Science and Humanities

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01_title.pdfAttached File24.9 kBAdobe PDFView/Open
02_certificates.pdf339.85 kBAdobe PDFView/Open
03_abstract.pdf37.68 kBAdobe PDFView/Open
04_acknowledgement.pdf5.53 kBAdobe PDFView/Open
05_contents.pdf120.37 kBAdobe PDFView/Open
06_list_of_tables.pdf5.22 kBAdobe PDFView/Open
07_list_of_figures.pdf37.27 kBAdobe PDFView/Open
08_list_of_abbreviations.pdf200.75 kBAdobe PDFView/Open
09_chapter1.pdf445.12 kBAdobe PDFView/Open
10_chapter2.pdf737.06 kBAdobe PDFView/Open
11_chapter3.pdf209.56 kBAdobe PDFView/Open
12_chapter4.pdf438.58 kBAdobe PDFView/Open
13_chapter5.pdf1.13 MBAdobe PDFView/Open
14_chapter6.pdf824.49 kBAdobe PDFView/Open
15_conclusion.pdf142.41 kBAdobe PDFView/Open
16_references.pdf134.48 kBAdobe PDFView/Open
17_list_of_publications.pdf83.22 kBAdobe PDFView/Open


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