Effective crop categorization using wavelet transform based optimized long short-term memory technique
Pompapathi M. Khaleelahmed S. Jawarneh M. Naved M. Awasthy M. Kumar S.S. Omarov B. Raghuvanshi A.
June 2025Institute of Advanced Engineering and Science
Bulletin of Electrical Engineering and Informatics
2025#14Issue 32309 - 2318 pp.
Effective crop categorization is important for keeping track of how crops grow and how much they produce in the future. Gathering crop data on categories, regions, and space distribution in a timely and accurate way could give a scientifically sound reason for changes to the way crops are organized. Polarimetric synthetic aperture radar dataset provides sufficient information for accurate crop categorization. It is essential to classify crops in order to successfully. This article presents wavelet transform (WT) based optimizedlong short-term memory (LSTM) deep learning (DL) for effective crop categorization. Image denoising is performed by WT. Denoising algorithms for images attempt to find a middle ground between totally removing all of the image’s noise and preserving essential, signal-free components of the picture in their original state. After denoising of images, crop image classification is achieved by LSTM and support vector machine (SVM) algorithm. LSTM has achieved 99.5% accuracy.
Accuracy , Crop categorization , Deep learning , Long short-term memory , Noise removal , PolSar dataset , Wavelet transform
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Department of Information Technology, RVR & JC College of Engineering, Guntur, India
Department of Electrical and Computer Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, India
College of Information Technology, Amman Arab University, Amman, Jordan
Department of Business Analytics, Jaipuria Institute of Management, Noida, India
Department of Engineering and Technology, Bharati Vidyapeeth Deemed to be University, Pune, India
Department of Computer Science Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India
Al-Farabi Kazakh National University, International Information Technology University, Almaty, Kazakhstan
Department of Computer Engineering, Mahakal Institute of Technology, Ujjain, India
Department of Information Technology
Department of Electrical and Computer Engineering
College of Information Technology
Department of Business Analytics
Department of Engineering and Technology
Department of Computer Science Engineering
Al-Farabi Kazakh National University
Department of Computer Engineering
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