标题
Classification of Rice Diseases using Convolutional Neural Network Models
作者
关键词
-
出版物
Journal of The Institution of Engineers (India): Series B
Volume -, Issue -, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2022-02-07
DOI
10.1007/s40031-021-00704-4
参考文献
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- (2021) Muhammad Umer et al. Journal of Ambient Intelligence and Humanized Computing
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- (2021) L. Prabaharan et al. Journal of Ambient Intelligence and Humanized Computing
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- (2021) Varun Gupta et al. Journal of The Institution of Engineers (India): Series B
- Automatic methods for classification of visual based viral and bacterial disease symptoms in plants
- (2021) Rajesh Yakkundimath et al. International Journal of Information Technology (Singapore)
- Detection of rice plant diseases based on deep transfer learning
- (2020) Junde Chen et al. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
- Nitrogen Deficiency Prediction of Rice Crop Based on Convolutional Neural Network
- (2020) Prabira Kumar Sethy et al. Journal of Ambient Intelligence and Humanized Computing
- Hybrid convolutional neural network (CNN) and long-short term memory (LSTM) based deep learning model for detecting shilling attack in the social-aware network
- (2020) K. Vivekanandan et al. Journal of Ambient Intelligence and Humanized Computing
- Image recognition of four rice leaf diseases based on deep learning and support vector machine
- (2020) Feng Jiang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Rice Blast Disease Recognition Using a Deep Convolutional Neural Network
- (2019) Wan-jie Liang et al. Scientific Reports
- Multiple vehicle tracking and classification system with a convolutional neural network
- (2019) HyungJun Kim Journal of Ambient Intelligence and Humanized Computing
- Predicting rice blast disease: machine learning versus process-based models
- (2019) David F. Nettleton et al. BMC BIOINFORMATICS
- Robust retinal blood vessel segmentation using convolutional neural network and support vector machine
- (2019) Kishore Balasubramanian et al. Journal of Ambient Intelligence and Humanized Computing
- Evaluation of image processing technique in identifying rice blast disease in field conditions based on KNN algorithm improvement by K‐means
- (2019) Mohammad Reza Larijani et al. Food Science & Nutrition
- Image processing based rice plant leaves diseases in Thanjavur, Tamilnadu
- (2018) T. Gayathri Devi et al. Cluster Computing-The Journal of Networks Software Tools and Applications
- Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network
- (2018) Wei Wang et al. Journal of Ambient Intelligence and Humanized Computing
- Identification of rice diseases using deep convolutional neural networks
- (2017) Yang Lu et al. NEUROCOMPUTING
- Detecting Bakanae disease in rice seedlings by machine vision
- (2016) Chia-Lin Chung et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Hyperspectral image analysis based on BoSW model for rice panicle blast grading
- (2015) Shuangping Huang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Rice diseases classification using feature selection and rule generation techniques
- (2012) Santanu Phadikar et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
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