Intelligent Agents System for Vegetable Plant Disease Detection Using MDTW-LSTM Model
- Title
- Intelligent Agents System for Vegetable Plant Disease Detection Using MDTW-LSTM Model
- Creator
- Chaturvedi A.; Nadgaundi S.K.; Raja M.K.; Dubey V.R.; Singhal A.; Gupta V.
- Description
- When it comes to agricultural output, nation, India, ranks first in the world, and agriculture is unparalleled. The need to categorize and trade agricultural goods is paramount. Manual organization, which is tedious and laborious, is not a choice. When agricultural products are graded automatically, a lot of time is saved. The application of image processing techniques facilitates the examination and evaluation of the products. A technique for identifying diseased vegetables is the focus of this effort. Feature extraction, preprocessing, segmentation, and training the model are all heavily dependent on sequence. Among the preprocessing technologies at disposal are image segmentation and filtering. Using Kapur's thresholding based segmentation method, the image's sick areas can be located during the segmentation process. Use k-means clustering for feature extraction to identify vegetable plant diseases. The training of an MDTW-LSTM model relies heavily on feature selection. In terms of performance, the proposed method surpasses two cutting-edge algorithms: LSTM and DTW. The results showed an accuracy of 97.35 percent, indicating a remarkable improvement. 2024 IEEE.
- Source
- 2024 3rd International Conference for Innovation in Technology, INOCON 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Dynamic Time Warping (DTW); Long Short Term Memory (LSTM); Plant Disease Detection
- Coverage
- Chaturvedi A., Gla University, Department of Electronics and Communication Engineering, Uttar Pradesh, Mathura, India; Nadgaundi S.K., Bharati Vidyapeeth College of Engineering, Instrumentation Engineering Department, Navi Mumbai, India; Raja M.K., Sri Eshwar College of Engineering, Department of Computer Science and Engineering, Coimbatore, India; Dubey V.R., Jai Narain College of Technology, Department of Computer Science and Engineering, Lambakheda, Bhopal, India; Singhal A., Christ (Deemed to Be University), School of Sciences, Delhi-NCR, Uttar Pradesh, Ghaziabad, India; Gupta V., Christ (Deemed to Be University), School of Sciences, Delhi-NCR, Uttar Pradesh, Ghaziabad, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835038193-1
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Chaturvedi A.; Nadgaundi S.K.; Raja M.K.; Dubey V.R.; Singhal A.; Gupta V., “Intelligent Agents System for Vegetable Plant Disease Detection Using MDTW-LSTM Model,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19452.