Modified-Project-Tomato

This is a modified Github project that uses Convolutional Neural Network (CNN) models to identify and classify healthy tomato plants. The goal of this project is to provide a tool that can help farmers and gardeners detect diseases from the tomato leaves early on, prevent crop loss, and improve the overall health of their tomato plants.

Steps to run

• All you need to run this project is a Google colab notebook.
• Here is the link to colab notebook: https://colab.research.google.com/drive/1MtqiaRlYIEEUnt7zO3SdGoDpQ4oS0a9u?usp=sharing
• Make a copy of the file, You can do so by File -> Save a copy on Drive

Credit to the code

https://github.com/redwankarimsony/project-tomato

@article{ahmed2022less,  
        author={Ahmed, Sabbir and Hasan, Md. Bakhtiar and Ahmed, Tasnim and Sony, Md. Redwan Karim and Kabir, Md. Hasanul},  
        journal={{IEEE Access}},   
        title={{Less is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease Classification}},   
        year={2022},  
        volume={},  
        number={},  
        pages={1-1},  
        doi={10.1109/ACCESS.2022.3187203},
        url={https://ieeexplore.ieee.org/document/9810234},
        publisher={{IEEE}}
        }

Visit the above link for indepth look at the paper and more information on the model.

Model summary

The model has a(n):

• Loss metric of 16.18
• Accuracy metric of 95.32
• MSE of 29.61148452758789