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About Flower Image Classification Using Deep Convolutional Neural Network
This document describes a method for classifying 102 types of flower images using a deep convolutional neural network called DenseNet121. The researchers used transfer learning by fine-tuning a pretrained DenseNet121 model on the Oxford 102 flower dataset. They preprocessed the images by normalizing and resizing them before feeding them to the fine-tuned model. Using this approach, they achieved a classification accuracy of 98.6% which is higher than other deep learning methods on this dataset.
Detailed Information
| Author: | ['ahmed'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 5 |
| Language: | English |
| Format: | |
| Price: | FREE |
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