KI:STE E-Learning

Lessons

Application for solar enery using transfer learning from the pre-trained neural network

3:49

Significance of trade wind cumulus clouds & their organizational variability over tropics

4:33

Visual features of cloud organizations and exploiting them to capture the diversity

5:35

Finding optimal boundary conditions in the continous space

5:59

Extension of agreement between humans and machines for the identified cloud organizations

6:37

Capturing transition in cloud organziations

1:44

Dry - wet atmospheric intrusions

5:23

Importance of Satellite Cloud Remote Sensing

10:58

Satellite Cloud Remote Sensing Introduction

15:27

How can machine learning help cloud research?

24:59

Satellite Cloud Remote Sensing Introduction

In this video, we will dive into how machine learning can help interpreting satellite measurements of clouds.

Lecturer

s

•

Dwaipayan Chatterjee

•

Prof.in Dr.in Susanne Crewell

•

Dr. Christoph Böhm

Lessons

Importance of cloud systems for Climate change and Renweable energy

Past state-of-the-art research studies and possible limitations

Deep learning Architecture and evolution of understanding

Integrating physical knowledge to find optimzed classes

Gaining inference of the identified classes by the neural network

Generalization: How does the network perform on unseen data

Application for solar enery using transfer learning from the pre-trained neural network

Significance of trade wind cumulus clouds & their organizational variability over tropics

Visual features of cloud organizations and exploiting them to capture the diversity

Finding optimal boundary conditions in the continous space

Extension of agreement between humans and machines for the identified cloud organizations

Capturing transition in cloud organziations

Dry - wet atmospheric intrusions

Importance of Satellite Cloud Remote Sensing

Satellite Cloud Remote Sensing Introduction

How can machine learning help cloud research?

Satellite Cloud Remote Sensing Introduction

Lecturer

s

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