A Novel method to detect Disease in leaf using Deep Learning Approach
| Autor: | V Kavin, D. Devi, K.R Lakshmi prabha., V Keerthana, S. Sophia |
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| Rok vydání: | 2021 |
| Předmět: |
010302 applied physics
Artificial neural network business.industry Computer science Deep learning fungi food and beverages 02 engineering and technology Agricultural engineering 021001 nanoscience & nanotechnology 01 natural sciences Convolutional neural network Plant disease Object detection Identification (information) Agriculture 0103 physical sciences Artificial intelligence Agricultural productivity 0210 nano-technology business |
| Zdroj: | 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS). |
| DOI: | 10.1109/icaccs51430.2021.9441892 |
| Popis: | Agricultural productivity depends heavily on the economy. This stands as the main reason for the detection of the plant disease in the field of agriculture, because diseases in plants are quite natural. Crop diseases serve as a major food supply threat. The identification of diseases can lead to more rapid interventions in order to reduce the effects of plant disease. Automatic detection of plant leaf disease is beneficial because of the limited requirement of overviewing in large areas of crops and detects the diseases at an earliest, i.e., when they attack the plant leaves. The performance and accuracy level were quite low in existing system. Modern developments in deep learning have made drastic improvements in accuracy of object recognition. The proposed study aims at classifying the defect in the leaves of different plants using the plant leaf image. This is achieved using Faster Region based convolution neural network. The proposed method has the potential to identify various diseases possible in the plants. |
| Databáze: | OpenAIRE |
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