DEEP BELIEF NETWORK BASED DISEASE DETECTION IN PEPPER LEAF FOR FARMING SECTOR.

More than a decade, the leaf was affected with various disease in farming of various crops which directly degrades the crop yield in agriculture leads to huge loss. It is necessary to detect various disease which affect the leaf and to take precautionary actions to increase the crop yield. In this p...

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Publicado en:Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 994 - 1003
Autores principales: JANA, S., BEGUM, A. RIJUVANA, SELVAGANESAN, S., SURESH, P.
Formato: equations & formulas pictorial tables/charts Journal Article
Publicado: Turkish Journal of Physiotherapy & Rehabilitation 2021
Acceso en línea:Ver este registro en EBSCOhost
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        atl: DEEP BELIEF NETWORK BASED DISEASE DETECTION IN PEPPER LEAF FOR FARMING SECTOR.
      aug:
        au:
          JANA, S.
          BEGUM, A. RIJUVANA
          SELVAGANESAN, S.
          SURESH, P.
        affil: Dept. of ECE, Veltech Rangarajan Dr Sagunthala R & D Institute of Science and Technology, Chennai-600062, Tamilnadu, India
      sug:
        subj:
          Neural Networks (Computer)
          Plant Leaves
          Agriculture
          Deep Learning
          Plants, Edible
      ab: More than a decade, the leaf was affected with various disease in farming of various crops which directly degrades the crop yield in agriculture leads to huge loss. It is necessary to detect various disease which affect the leaf and to take precautionary actions to increase the crop yield. In this paper an automated system is proposed with imaging techniques (acquisition, feature extraction, classification). The real time image is analyzed with Deep Belief Network classifier to automate the various disease from the training data sets with the predefined data sets. The results reported in this article give better performance over the existing methods which directly having relation to increase the crop yields.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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