265 - Feature engineering or deep learning (for semantic segmentation)

Code generated in the video can be downloaded from here:
github.com/bns...
What is a better approach when working with small training data for semantic segmentation? Is it deep learning such as U-net or is it feature extraction followed by machine learning classification (e.g., Random Forest, LGBM, XGBoost, SVM, etc.)?