• DocumentCode
    603563
  • Title

    Plant recognition system based on Neural Networks

  • Author

    Rankothge, W.H. ; Dissanayake, D.M.S.B. ; Gunathilaka, U.V.K.T. ; Gunarathna, S.A.C.M. ; Mudalige, C.M. ; Thilakumara, R.P.

  • Author_Institution
    Sri Lanka Inst. of Inf. Technol., Malabe, Sri Lanka
  • fYear
    2013
  • fDate
    23-25 Jan. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    With the evolution of technologies, people have adopted their day today lives to utilize the benefits of highly advanced technologies. Artificial Intelligence and Neural Networks are playing major roles in this process and they have been involved in fields of medicine, automobiles, aeronautical science, military and many more. Unfortunately very little concern is devoted to the botanical science field, especially in taxonomic researches of plants. Even today, identification and classification of unknown plant species are performed manually by expert personnel who are very few in number. It takes a long time and the results are not very accurate. Advanced Plant Identification System (APIS) is an intelligent system which has the ability to identify tree species from photographs of their leaves and it provides more accurate results within less time.
  • Keywords
    artificial intelligence; biological techniques; biology computing; botany; feature extraction; image processing; neural nets; APIS; advanced plant identification system; aeronautical science; artificial intelligence; automobiles; botanical science field; leaves; medicine; military; neural networks; photographs; plant recognition system; plant taxonomic research; tree species; Biological neural networks; Feature extraction; Image color analysis; Servers; Training; Artificial Intelligence; Neural Networks; Pattern Recognition; Plant Identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Technology and Engineering (ICATE), 2013 International Conference on
  • Conference_Location
    Mumbai
  • Print_ISBN
    978-1-4673-5618-3
  • Type

    conf

  • DOI
    10.1109/ICAdTE.2013.6524735
  • Filename
    6524735