"Transferability of Machine Learning Models for Crop Classification in ..."

Hauke Hoppe et al. (2024)

> Home

Details and statistics

DOI: 10.3390/RS16091493

access: open

type: Journal Article

metadata version: 2024-06-18

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/remotesensing/HoppeDMWNLWB24
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/remotesensing/HoppeDMWNLWB24
Hauke Hoppe, Peter Dietrich, Philip Marzahn, Thomas Weiß, Christian Nitzsche, Uwe Freiherr von Lukas, Thomas Wengerek, Erik Borg:
Transferability of Machine Learning Models for Crop Classification in Remote Sensing Imagery Using a New Test Methodology: A Study on Phenological, Temporal, and Spatial Influences. Remote. Sens. 16(9): 1493 (2024)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.