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Introduction
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Classroom Contents
3D U-Net for Semantic Segmentation
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- 1 Introduction
- 2 Data types
- 3 Why 3D UNet
- 4 Unit Architecture
- 5 Python libraries
- 6 Annotation
- 7 Notebook
- 8 Running the code
- 9 Verify tensorflow and Keras
- 10 Import data
- 11 Local file location
- 12 Number of classes
- 13 Image dimensions
- 14 Multiclass classification
- 15 Learning rate
- 16 Preprocessing
- 17 Results
- 18 Testing
- 19 Saving
- 20 Multichannel
- 21 Basic segmentation
- 22 Final segmentation
- 23 OEM TIFF
- 24 Multichannel image
- 25 Summary
