50 Cities to visit before you classify - A world-wide multi-modal dataset for semantic segmentation of remote sensing imagery

Weitzel, Kenneth and Zabielski, Bruno and Heinrich, Johannes and Hänsch, Ronny (2026) 50 Cities to visit before you classify - A world-wide multi-modal dataset for semantic segmentation of remote sensing imagery. In: CVPR2026 workshop proceedings. EarthVision, 2026-06-04, Denver, USA.

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Item URL in elib:

https://elib.dlr.de/224321/

Document Type:

Conference or Workshop Item (Speech, Poster)

Title:

50 Cities to visit before you classify - A world-wide multi-modal dataset for semantic segmentation of remote sensing imagery

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Weitzel, Kenneth	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Zabielski, Bruno	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Heinrich, Johannes	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Hänsch, Ronny	Ronny.Haensch (at) dlr.de	https://orcid.org/0000-0002-2936-6765	UNSPECIFIED

Date:

2026

Journal or Publication Title:

CVPR2026 workshop proceedings

Refereed publication:

Yes

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

Deep Learning, Benchmark, Dataset

Event Title:

EarthVision

Event Location:

Denver, USA

Event Type:

international Conference

Event Date:

4 June 2026

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

Earth Observation

DLR - Research area:

Raumfahrt

DLR - Program:

R EO - Earth Observation

DLR - Research theme (Project):

R - Artificial Intelligence

Location:

Oberpfaffenhofen

Institutes and Institutions:

Microwaves and Radar Institute > SAR Technology

Deposited By:

Hänsch, Ronny

Deposited On:

06 May 2026 14:45

Last Modified:

02 Jul 2026 14:35

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