Rice Paddy Disease Detection and Disease Affected Area Segmentation Using Convolutional Neural Networks

Mashroor, Fahim; Ishrak, Ibne Farhan; Alvee, Sajan Mahmud; Jahan, A.S.M. Nawroz; Suvon, Md Naimul Islam; Siddique, Shahnewaz

doi:10.1109/tencon54134.2021.9707192

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Rice Paddy Disease Detection and Disease Affected Area Segmentation Using Convolutional Neural Networks

Cited by 4 publications

References 19 publications

Multimodal Paddy Leaf Diseases Detection Using Feature Extraction and Machine Learning Techniques

Multimodal Paddy Leaf Diseases Detection Using Feature Extraction and Machine Learning Techniques

Heuristically Improvised rice disease classification framework based on adaptive segmentation with the fusion of LSTM layer into Multi-Scale Residual attention Network

Paddy Leaf Disease Classification Using EfficientNet B4 With Compound Scaling and Swish Activation: A Deep Learning Approach

Contact Info

Product

Resources

About