Cloud Base Height Estimation Using Stereo All-Sky Imagery and Deep Learning

Weiler, Franka (2025) Cloud Base Height Estimation Using Stereo All-Sky Imagery and Deep Learning. Bachelor's, Technische Universität München.

PDF - Only accessible within DLR
12MB

Item URL in elib:

Document Type:

Thesis (Bachelor's)

Title:

Cloud Base Height Estimation Using Stereo All-Sky Imagery and Deep Learning

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Weiler, Franka	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED

DLR Supervisors:

Contribution	DLR Supervisor	Institution or E-Mail	DLR Supervisor's ORCID iD
Thesis advisor	Fabel, Yann	UNSPECIFIED	https://orcid.org/0000-0002-1892-5701

Date:

October 2025

Open Access:

Number of Pages:

Status:

Unpublished

Keywords:

All-Sky Imager, Cloud Base Height, Ceilometer, Machine Learning

Institution:

Technische Universität München

HGF - Research field:

Energy

HGF - Program:

Materials and Technologies for the Energy Transition

HGF - Program Themes:

High-Temperature Thermal Technologies

DLR - Research area:

Energy

DLR - Program:

E SW - Solar and Wind Energy

DLR - Research theme (Project):

E - Condition Monitoring

Location:

Köln-Porz

Institutes and Institutions:

Deposited By:

Fabel, Yann

Deposited On:

05 Nov 2025 13:10

Last Modified:

05 Nov 2025 13:10

Repository Staff Only: item control page