Automated Leaf Disease Diagnosis with Deep Learning

Automated Leaf Disease Diagnosis with Deep Learning

Sakshi Abhale1, Shrutika Bhavsar2, Kadambari Ghadge3, Akash Sale4

1 Electronics & Telecommunication, Sinhgad Institute of Technology and Science, Narhe, Pune

2Electronics & Telecommunication, Sinhgad Institute of Technology and Science, Narhe, Pune

3Electronics & Telecommunication, Sinhgad Institute of Technology and Science, Narhe, Pune

4Electronics & Telecommunication, Sinhgad Institute of Technology and Science, Narhe, Pune

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Abstract - Agriculture is crucial for India's economy, but one problem is identifying plant diseases, especially in remote areas where contacting experts is difficult. Wrong disease identification can lead to crop loss. Even government agriculture departments sometimes give incorrect advice to farmers. To tackle this, a dataset of apple crop images has been created to help identify healthy and diseased leaves accurately. These images come from different angles and directly from apple fields. The early disease detection in agriculture, particularly focusing on diseases affecting apple crops. Specifically, it mentions diseases like early blight, late blight, black scurf, common scab that can affect apple plants. It discusses using automatic methods like Convolutional Neural Networks (CNN) to detect and classify these diseases based on a dataset. The approach involves automatic feature extraction and classification using colur information.