Prediction of diseased rice plant using video processing and LSTM-simple recurrent neural network with comparative study
- 23 June 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Multimedia Tools and Applications
- Vol. 80 (19), 29267-29298
- https://doi.org/10.1007/s11042-021-10889-x
Abstract
No abstract availableKeywords
This publication has 69 references indexed in Scilit:
- Deep learning models for plant disease detection and diagnosisComputers and Electronics in Agriculture, 2018
- Weed detection in soybean crops using ConvNetsComputers and Electronics in Agriculture, 2017
- Particle Swarm Optimization based incremental classifier design for rice disease predictionComputers and Electronics in Agriculture, 2017
- Expert system for diagnosis pests and diseases of the rice plant using forward chaining and certainty factor methodPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Plant Species Recognition Based on Deep Convolutional Neural NetworksLecture Notes in Computer Science, 2017
- Symptom based automated detection of citrus diseases using color histogram and textural descriptorsComputers and Electronics in Agriculture, 2017
- An improved moth flame optimization algorithm based on rough sets for tomato diseases detectionComputers and Electronics in Agriculture, 2017
- Expert system for diagnosis of diseases of rice plants: Prototype design and implementationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Improved Computation for Levenberg–Marquardt TrainingIEEE Transactions on Neural Networks, 2010
- Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review]IEEE Transactions on Automatic Control, 1997