https://github.com/hchandeepa/common_rice_disease_detector
Common Rice Diseases Detector
https://github.com/hchandeepa/common_rice_disease_detector
artificial-intelligence cnn deep-learning jupyter-notebook machine-learning neural-networks python
Last synced: about 2 months ago
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Common Rice Diseases Detector
- Host: GitHub
- URL: https://github.com/hchandeepa/common_rice_disease_detector
- Owner: HChandeepa
- License: mit
- Created: 2024-02-02T09:34:35.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-05T07:38:27.000Z (7 months ago)
- Last Synced: 2025-03-26T17:11:21.506Z (2 months ago)
- Topics: artificial-intelligence, cnn, deep-learning, jupyter-notebook, machine-learning, neural-networks, python
- Language: Jupyter Notebook
- Homepage:
- Size: 178 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 2
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
The "Common Rice Disease Detector" effort aims to tackle the vital problem of rice crop
health, which has a substantial effect on the security of food worldwide. By providing
farmers and agricultural specialists with a tool for quickly and accurately identifying common
rice illnesses, this research hopes to reduce losses in rice quality and output. Among our goals
is the creation of a user-friendly application for data analysis and image recognition using
deep learning methods, including Convolutional Neural Networks (CNNs). By taking a
picture of a leaf, users can quickly and accurately diagnose rice illnesses thanks to the usage
of a smartphone application. We were able to precisely classify both healthy leaves and
illnesses such as Hispa, Brownspot, and leaf blast by utilizing CNNs.
As part of the research approach, photos of healthy and sick rice leaves were collected from
Kaggle. React was used in the development of the mobile app prototype, which integrated the
CNN illness detection algorithm. Although the three diseases stated above are the main
emphasis of this version, future updates will try to add more rice diseases to the app's
capabilities. Through the provision of current and useful information to stakeholders, this
effort helps to improve food security through crop management methods.