Hybrid Machine Learning Algorithm-Based Paddy Leave Disease Detection System

The agriculture field is one of the current examination subjects is classification, detection, and recognition of paddy leave disease images of a plant. The research methodology gives paddy leave image Acquisition, paddy leaf disease pre-processing, Segmentation, and MSVM Classification method of pa...

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Veröffentlicht in:2020 International Conference on Smart Electronics and Communication (ICOSEC) S. 512 - 519
Hauptverfasser: Payal, Kukana, Poonam
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.09.2020
Schlagworte:
Agriculture
Conferences
Deep Neural Network
Diseases
Image color analysis
Image segmentation
Jaya-DNN and MSVM (Multi Support Vector Machine)
Microorganisms
Paddy Leave Detection
Support vector machines
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Zusammenfassung:The agriculture field is one of the current examination subjects is classification, detection, and recognition of paddy leave disease images of a plant. The research methodology gives paddy leave image Acquisition, paddy leaf disease pre-processing, Segmentation, and MSVM Classification method of paddy Leave diseases. It is employing the OMSVM classification method, the Paddy Leave Disease images are classifying or detecting and calculated the accuracy rate and reduce the error rates such as FDR and TNR parameters. The research parameter has attained the accuracy rate of up to 98.8 per cent, TPR up to 0.99 per cent, TNR up to 0.9910 percent, FDR value up to 0.0029 percent and FPR value up to 0.0090 percent and compared with existing parameters and methods.
DOI:10.1109/ICOSEC49089.2020.9215367