Module 4: Feature Extraction and Band Selection

by NSTC NSTC

July 4, 2026

About Module 4: Feature Extraction and Band Selection

Module Content

Module 4: Feature Extraction and Band Selection

9 Lessons

Chapter 4.1: Preparing Hyperspectral Data for AI

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Lesson 1:  Lesson 4.1.1: Structuring hyperspectral data for model training

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Lesson 2:  Lesson 4.1.2: Labeling healthy and diseased crop samples

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Lesson 3:  Lesson 4.1.3: Training, validation and testing data preparation

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Chapter 4.2: Spectral Feature Extraction

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Lesson 1:  Lesson 4.2.1: Extracting spectral features from hyperspectral data

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Lesson 2:  Lesson 4.2.2: Vegetation indices for crop stress detection

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Lesson 3:  Lesson 4.2.3: Statistical features for disease classification

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Chapter 4.3: Band Selection Techniques

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Lesson 1:  Lesson 4.3.1: Importance of dimensionality reduction

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Lesson 2:  Lesson 4.3.2: Correlation-based and PCA-based band selection

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Lesson 3:  Lesson 4.3.3: Identifying disease-sensitive spectral bands

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