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About Rice Leaf Diseases Classification Using CNN With
This document summarizes a research paper presented at the 2020 IEEE Calcutta Conference titled "Rice Leaf Diseases Classification Using CNN With Transfer Learning". The paper proposes a CNN model using transfer learning with VGG-16 to classify rice leaf diseases. The authors collected their own dataset of rice leaf images which is small in size, so they used transfer learning to develop their deep learning model. Their proposed CNN architecture fine-tuned the fully connected layers of VGG-16 to classify diseases in their dataset. Their model achieved an accuracy of 92.46% in classifying common rice diseases like leaf blast, leaf blight, and brown spot.
Detailed Information
| Author: | ['Tefe'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 7 |
| Language: | English |
| Format: | |
| Price: | FREE |
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