Rice Blast Disease Recognition Using a Deep Convolutional Neural Network
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Rice Blast Disease Recognition Using a Deep Convolutional Neural Network
Authors
Keywords
-
Journal
Scientific Reports
Volume 9, Issue 1, Pages -
Publisher
Springer Nature
Online
2019-02-27
DOI
10.1038/s41598-019-38966-0
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Plant tonic, a plant-derived bioactive natural product, exhibits antifungal activity against rice blast disease
- (2018) Farnaz Abed-Ashtiani et al. INDUSTRIAL CROPS AND PRODUCTS
- A hybrid deep learning CNN–ELM for age and gender classification
- (2018) Mingxing Duan et al. NEUROCOMPUTING
- Identification of rice diseases using deep convolutional neural networks
- (2017) Yang Lu et al. NEUROCOMPUTING
- Localization and diagnosis framework for pediatric cataracts based on slit-lamp images using deep features of a convolutional neural network
- (2017) Xiyang Liu et al. PLoS One
- Automatic moth detection from trap images for pest management
- (2016) Weiguang Ding et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A deep feature based framework for breast masses classification
- (2016) Zhicheng Jiao et al. NEUROCOMPUTING
- Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security
- (2016) Min-Joo Kang et al. PLoS One
- Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network
- (2016) Ziyi Liu et al. Scientific Reports
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks
- (2015) Petros-Pavlos Ypsilantis et al. PLoS One
- Investigating the impact of rice blast disease on the livelihood of the local farmers in greater Mwea region of Kenya
- (2013) Joseph Kihoro et al. SpringerPlus
- Rice diseases classification using feature selection and rule generation techniques
- (2012) Santanu Phadikar et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Effect of Foliar and Root Application of Silicon Against Rice Blast Fungus in MR219 Rice Variety
- (2012) Farnaz Abed-Ashtiani et al. Plant Pathology Journal
- LIBSVM
- (2012) Chih-Chung Chang et al. ACM Transactions on Intelligent Systems and Technology
- A novel hybrid CNN–SVM classifier for recognizing handwritten digits
- (2011) Xiao-Xiao Niu et al. PATTERN RECOGNITION
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now