Home
All Courses
About
Partner
All Courses
•
AI for cloud classification
•
Generalization: How does the network perform on unseen data
Back to course
Back to all courses
Lessons
Importance of cloud systems for Climate change and Renweable energy
4:00
Past state-of-the-art research studies and possible limitations
3:48
Deep learning Architecture and evolution of understanding
4:20
Integrating physical knowledge to find optimzed classes
4:48
Gaining inference of the identified classes by the neural network
4:11
Generalization: How does the network perform on unseen data
2:59
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
Generalization: How does the network perform on unseen data
In this video we will talk about generalization capacity of the trained neural network
Lecturer
s
•
Dwaipayan Chatterjee
•
Prof.in Dr.in Susanne Crewell
•
Dr. Christoph Böhm
Additional Material
Additional Material
Additional Material
