GLCM and LSTM Recurrent Neural Networks Integrated with Machine Learning Techniques to Identify Plant Disease
Nithyananda B Devadiga1, Akshatha K N2
1Nithyananda B Devadiga, Department of Computer Science, R N Shetty PU College, Kundapura (Karnataka), India.
2Akshatha K N, Department of Botany, RN Shetty PU College, Kundapura (Karnataka), India.
Manuscript received on 28 July 2022 | Revised Manuscript received on 01 August 2022 | Manuscript Accepted on 15 August 2022 | Manuscript published on 30 August 2022. | PP: 44-46 | Volume-11 Issue-9, August 2022. | Retrieval Number: 100.1/ijitee.G92430811922 | DOI: 10.35940/ijitee.G9243.0811922
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Abstract: Plant diseases are very impactful towards the overall effectiveness and quality management of the agricultural sector. In recent years, deep learning methods have been used as a way to identify these diseases, based on neural networks. The study presents GLCM and LSTM Recurrent Neural Networks Integrated with Machine Learning towards the identification of plant diseases. It has been found that the process is very accurate and can assess diverse plants disease characteristics dataset as well.
Keywords: GLCM and LSTM System, Deep Learning, RNN, Plant Disease Identification
Scope of the Article: Deep Learning