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AI For Crop Disease Detection using Hyperspectral imaging
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Module 6: Deep Learning for Hyperspectral Disease Analysis

Module 6: Deep Learning for Hyperspectral Disease Analysis

by NSTC NSTC

July 4, 2026

About Module 6: Deep Learning for Hyperspectral Disease Analysis

Module Content

Module 6: Deep Learning for Hyperspectral Disease Analysis

9 Lessons

Chapter 6.1: Introduction to Deep Learning

Lesson 1: Lesson 6.1.1: Why deep learning is useful for hyperspectral data

Lesson 2: Lesson 6.1.2: Neural networks for spectral classification

Lesson 3: Lesson 6.1.3: Overfitting, dropout and regularization

Chapter 6.2: CNN-Based Hyperspectral Analysis

Lesson 1: Lesson 6.2.1: 1D CNN for spectral feature learning

Lesson 2: Lesson 6.2.2: 2D CNN for spatial feature learning

Lesson 3: Lesson 6.2.3: 3D CNN for spatial-spectral hyperspectral analysis

Chapter 6.3: ML vs Deep Learning Model Comparison

Lesson 1: Lesson 6.3.1: Comparing traditional ML and deep learning models

Lesson 2: Lesson 6.3.2: Choosing the right model for crop disease detection

Lesson 3: Lesson 6.3.3: Interpreting performance differences across models

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