DL BASED DISEASE CLASSIFICATION

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  Testing the diseased leave by the improved model with higher datasets

Inspiration

The inspiration for the project stems from the pressing need to address critical challenges in agriculture, such as pesticide overuse, cost inefficiencies, and environmental degradation. By harnessing the power of technology, including YOLO-based object detection and machine learning, we draw inspiration from the potential to revolutionize the way we protect our crops and sustainably manage agricultural resources. Our inspiration is driven by the desire to create a more environmentally conscious and efficient approach to farming, ensuring food security, reducing environmental impact, and fostering a brighter future for agriculture and the planet.

Challenges we ran into

Noises and poor training

Accomplishments that we're proud of

Improved model by(data augmentation, epoch ,increased datasets

What we learned

We learned about the ml and dl and yolo, Agri fields, Pesticides used ,OpenCV ,team management

What's next for DL BASED DISEASE CLASSIFICATION

Built With

• deeplearning
• machine-learning
• opencv
• python
• yolo