Applying Permutation Channel Importance (PCI) to a Remote Sensing Model | Python Tutorial

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We dive into Permutation Channel Importance (PCI) and show you how to apply it using Python. We'll work with the Landsat Irish Coastal Segmentation (LICS) Dataset, a resource for advancing deep learning methods in coastal water body segmentation. This dataset includes 100 multispectral test images, each with a binary segmentation mask that classifies pixels as either land or ocean. This is a great start if you are interested in applying Explainable AI methods to remote sensing machine learning models.

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XAI for CV:    • XAI for CV  
XAI:    • Explainable AI (XAI)  
SHAP:    • SHAP  
Algorithm fairness:    • Algorithm Fairness  

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🚀 Chapters 🚀
00:00 Introduction
01:43 Landsat Irish Coastal Segmentation (LICS) dataset
02:54 Exploring LICS
09:58 Shuffling a channel
12:53 Applying PCI