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About Image Classification Based On Transfer Learning of CNN
The document summarizes a study that used transfer learning with convolutional neural networks (CNNs) for image classification. Specifically, it first extracted histogram of oriented gradient (HOG) features from training images and used a support vector machine (SVM) for pre-classification. It then used the pre-classification results to train the weights of a CNN, creating a transfer learning model. This model was able to classify new images with improved accuracy of around 95% compared to traditional classifiers or CNNs alone, demonstrating around a 5% improvement in classification accuracy.
Detailed Information
| Author: | ['Prateek Singh'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 5 |
| Language: | English |
| Format: | |
| Price: | FREE |
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