Lukas Liebel

Technische Universität München

H-index: 10

Europe-Germany

About Lukas Liebel

Lukas Liebel, With an exceptional h-index of 10 and a recent h-index of 9 (since 2020), a distinguished researcher at Technische Universität München, specializes in the field of Computer Vision, Deep Learning, Autonomous Driving, Remote Sensing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Derivation of Geometrically and Semantically Annotated UAV Datasets at Large Scales from 3D City Models

Comparison of monocular depth estimation methods using geometrically relevant metrics on the IBims-1 dataset

Multitask learning for human settlement extent regression and local climate zone classification

Long-short skip connections in deep neural networks for dsm refinement

A Generalized Multi-Task Learning Approach to Stereo DSM Filtering in Urban Areas

Weakly supervised semantic segmentation of satellite images for land cover mapping--challenges and opportunities

Lukas Liebel Information

University	Technische Universität München
Position	___
Citations(all)	637
Citations(since 2020)	598
Cited By	198
hIndex(all)	10
hIndex(since 2020)	9
i10Index(all)	10
i10Index(since 2020)	9
Email	Access Email
University Profile Page	Technische Universität München
Google Scholar	View Google Scholar Profile

Lukas Liebel Skills & Research Interests

Computer Vision

Deep Learning

Autonomous Driving

Remote Sensing

Top articles of Lukas Liebel

Title	Journal	Author(s)	Publication Date
Derivation of Geometrically and Semantically Annotated UAV Datasets at Large Scales from 3D City Models		Sidi Wu Lukas Liebel Marco Körner	2021/1/10
Comparison of monocular depth estimation methods using geometrically relevant metrics on the IBims-1 dataset	Computer vision and image understanding	Tobias Koch Lukas Liebel Marco Körner Friedrich Fraundorfer	2020/2/1
Multitask learning for human settlement extent regression and local climate zone classification	IEEE Geoscience and Remote Sensing Letters	Chunping Qiu Lukas Liebel Lloyd Haydn Hughes Michael Schmitt Marco Körner ...	2020/11/24
Long-short skip connections in deep neural networks for dsm refinement	The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences	Ksenia Bittner Lukas Liebel Marco Körner Peter Reinartz	2020/8/12
A Generalized Multi-Task Learning Approach to Stereo DSM Filtering in Urban Areas	ISPRS Journal of Photogrammetry and Remote Sensing	Lukas Liebel Ksenia Bittner Marco Körner	2020/8/1
Weakly supervised semantic segmentation of satellite images for land cover mapping--challenges and opportunities		Michael Schmitt Jonathan Prexl Patrick Ebel Lukas Liebel Xiao Xiang Zhu	2020/2/19