Скачать или смотреть Module 5: Example 2 | Segmentation Models: Advanced Image Processing

In Module 5 of our Segmentation Models course, we delve into building models and understanding key metrics for evaluation. Explore the simple training pipeline, fine-tuning strategies, and techniques for training only the decoder while freezing the encoder to preserve pre-trained weights. Learn how to handle non-RGB data by either training from scratch or adding an extra convolution layer for mapping data to three channels.

Delve into essential metrics such as the Jaccard index (Intersection over Union) and F-score (Dice coefficient), crucial for assessing segmentation model performance. Understand the parameters involved in these metrics, including class weights, smoothness, per-image calculation, and thresholding. Join us as we unravel the complexities of building and evaluating segmentation models in this insightful module! 🏗️📊

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