From 3d99a6be95b8559090c0921877f6fafbeb38a356 Mon Sep 17 00:00:00 2001 From: Shashmitha V Date: Fri, 25 Oct 2024 22:33:12 +0530 Subject: [PATCH] Create README.md --- .../Crop Pest and Disease Detection/README.md | 27 +++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 Algorithms and Deep Learning Models/Crop Pest and Disease Detection/README.md diff --git a/Algorithms and Deep Learning Models/Crop Pest and Disease Detection/README.md b/Algorithms and Deep Learning Models/Crop Pest and Disease Detection/README.md new file mode 100644 index 000000000..0cda31812 --- /dev/null +++ b/Algorithms and Deep Learning Models/Crop Pest and Disease Detection/README.md @@ -0,0 +1,27 @@ +# Crop Pest and Disease Detection + +This repository contains machine learning algorithms and deep learning models designed to identify and classify pests and diseases affecting crops. Early detection of crop diseases and pests is crucial for maintaining agricultural health and maximizing yield. By leveraging various models, this project aims to assist farmers and agronomists in making timely interventions. + +## Features +- **Dataset Preparation**: Preprocessing and augmentation techniques to enhance model accuracy. +- **ML Algorithms**: Implementation of models like SVM, Random Forest, and KNN for pest and disease classification. +- **Deep Learning Models**: Convolutional Neural Networks (CNN) for advanced image recognition and classification. +- **Evaluation Metrics**: Accuracy, precision, recall, and F1-score to measure model performance. + +## Requirements +- Python 3.x +- TensorFlow, Keras, Scikit-learn, OpenCV, and other dependencies (see `requirements.txt`) + +## Usage +1. Clone the repository: + ```bash + git clone https://github.com/recodehive/machine-learning-repos +2. Install dependencies: + ```bash + pip install -r requirements.txt + +### Results +Detailed results, including accuracy and loss graphs, are available in the Results folder +[View Here](https://github.com/recodehive/machine-learning-repos/tree/main/Algorithms%20and%20Deep%20Learning%20Models/Crop%20Pest%20and%20Disease%20Detection/Model) + +