Plant Disease Classification

Ornamental Plant Disease Classification Model: This model detects and classifies various diseases that affect ornamental plants based on the dataset provided.
Plant Disease Dataset: This dataset contains images of different diseases that can affect ornamental plants.

References

This model leverages various resources for guidance and inspiration throughout the project, including:

1. Image Classification Tutorial by TensorFlow – Helped the team understand the basics of image classification.
2. Data Augmentation Tutorial by TensorFlow – Provided techniques for augmenting training data to reduce overfitting.
3. Animals Classification Kaggle Project – Served as a reference for classification techniques and model architecture.
4. RoseNet: Rose Leaf Dataset for the Development of an Automated System to Recognize Rose Diseases – Used as a scientific reference for rose disease classification.
5. An Extensive Sunflower Dataset for the Successful Identification and Classification of Sunflower Diseases – Used as a scientific reference for sunflower disease classification.

By following a structured approach and utilizing these relevant resources, the Machine Learning team aims to build an accurate and efficient model for classifying plant diseases.