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AI for landcover classification
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Contrastive self-supervised Learning
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Lessons

Introduction to Remote Sensing

4:50

Introduction to Land Cover Classification

22:43

Benchmark Dataset

4:00

Contrastive self-supervised Learning

4:31

Introduction to GEE via Code Snippets Walkthrough

5:14

Introduction to Atmospheric Transformation

4:24

Location-Based Labels

1:50

The Basic Idea of ASOS

1:48

The Neural Network Architecture and Training

1:53

Defining Occlusions Using the Activation Space

3:46

Interpretability of the Activation Space

1:06

The Advantages of ASOS

2:03

Datasets - AnthroProtect

3:58

Datasets - MapInWild

2:56

Datasets - TorchGeo

3:50

Datasets - BigEarthNet

3:30

Datasets - Eurosat

2:24

Spatial Data Split

2:50

Contrastive self-supervised Learning

Self-supervised learning is a method of machine learning where model learns from unlabeled data. In this video you will learn about contrastive learning, a type of self-supervised learning.

Lecturer

s

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Ankit Patnala
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Ribana Roscher
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Timo Stomberg

Additional Material

Additional Material

Additional Material

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