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- W4316658843 abstract "Groundnut is a significant oilseed crop in the world, and India is the second-largest producer of groundnuts. This crop can be attacked by several diseases that are predominant factors contributed towards the loss of degradation and productivity in the quality; leads to a low agricultural economy. Hence, there is a need to find more reliable and better automation solution to identify groundnut leaf disease. In this study, we propose an Automated Groundnut Leaf Disease Recognition using Whale Optimization Algorithm with Deep Learning (AGLDR-WOADL) technique. The presented AGLDR-WOADL technique comprises a series of operations. Primarily, threshold based segmentation is applied to identify the diseased portions of the image. Next, NASNet large feature extraction technique is exploited. Finally, the WOA with long short term memory (LSTM) method is utilized to recognize various kinds of plant diseases. To demonstrate the enhanced performance of the AGLDR-WOADL approach, an extensive range of simulations were performed. The comprehensive comparison study indicated the improved outcomes of the AGLDR-WOADL approach over other existing methods with higher accuracy of 99.63%." @default.
- W4316658843 created "2023-01-17" @default.
- W4316658843 creator A5007935648 @default.
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- W4316658843 date "2022-11-24" @default.
- W4316658843 modified "2023-10-11" @default.
- W4316658843 title "Automated Groundnut Leaf Disease Recognition Using Whale Optimization Algorithm with Deep Learning Model" @default.
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- W4316658843 doi "https://doi.org/10.1109/icaiss55157.2022.10010713" @default.
- W4316658843 hasPublicationYear "2022" @default.
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