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About Transfer Learning PDF
This document summarizes a research paper on transfer learning based image classification using convolutional neural networks (CNNs). The paper proposes using the feature extraction part of the Inception v3 CNN model to extract features from images. These features are then used to retrain only the classification layer for two datasets: Caltech101 and Oxford 17 Flowers. Transfer learning is used to keep the pretrained weights of the feature extraction layers fixed while retraining the classification layer. Testing on the datasets achieved 98% precision on Caltech101 and 92.27% precision on Oxford 17 Flowers.
Detailed Information
| Author: | ['ajaytiwari2779'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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