Usually training CNN costs us a lot of time and GPU cycles. One key technique to avoid this type of cost is "transfer learning". This example shows how we can try "transfer learning" using MATLAB. We combine pretrained model (alex net) and SVM to classify two similar flowers, "Dandelion" and "Colt's Foot".
通常CNNの学習には膨大な計算時間と計算コストがかかります。こうしたコストを避けるひとつの方法に転移学習と呼ばれる方法があります。このサンプルでは、よく似た2種類の花、タンポポとフキタンポポを学習済みのモデル(Alex Net)と SVM を組み合わせて見分けます。
引用
Eiji Ota (2024). CNN / Transfer Learning Example (https://www.mathworks.com/matlabcentral/fileexchange/57280-cnn-transfer-learning-example), MATLAB Central File Exchange. に取得済み.
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- Image Processing and Computer Vision > Computer Vision Toolbox > Recognition, Object Detection, and Semantic Segmentation >
- AI and Statistics > Statistics and Machine Learning Toolbox > Classification >
- AI and Statistics > Deep Learning Toolbox > Get Started with Deep Learning Toolbox >
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バージョン | 公開済み | リリース ノート | |
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1.5.0.0 | Fixed a bug related to activations function |
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1.4.0.0 | Changed source codes to use support package for alexnet. |
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1.3.0.0 | Added automatic setup script "setupScript.m".
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1.2.0.0 | Modified readme file. The instruction in the readme file was wrong. Sorry! Wrong : Create 2 Folders for 'Dandelion' and 'ColtsFoot' under 'ImageData'
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1.1.0.0 | Modified the readme file. Please check bug report, if you have troubles with this demo.
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1.0.0.0 |