- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
REFINEMENT OF CROPLAND DATA LAYER USING MACHINE LEARNING ; volume:XLII-3/W11 ; year:2020 ; pages:161-164
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLII-3/W11 (2020), 161-164
- Creator
-
Zhang, C.
Yang, Z.
Di, L.
Lin, L.
Hao, P.
- DOI
-
10.5194/isprs-archives-XLII-3-W11-161-2020
- URN
-
urn:nbn:de:101:1-2020022004115814132632
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:59 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Zhang, C.
- Yang, Z.
- Di, L.
- Lin, L.
- Hao, P.
Other Objects (12)
Validation and refinement of cropland map in southwestern China by harnessing ten contemporary datasets
Machine learning for application layer intrusion detection
Accelerating reliable multiscale quantum refinement of protein–drug systems enabled by machine learning
Machine Learning for Improving Surface-Layer-Flux Estimates
Efficient inverse design optimization through multi-fidelity simulations, machine learning, and boundary refinement strategies
Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations
Machine learning of surface layer property prediction for milling operations
Example-based decomposition, generalization and refinement for machine translation
Opening the machine learning black box with Layer-wise Relevance Propagation
On the estimation of boundary layer heights: a machine learning approach
Flow Characteristics of Fibrous Gas Diffusion Layers Using Machine Learning Methods
On the estimation of boundary layer heights: A machine learning approach
Validation and refinement of cropland map in southwestern China by harnessing ten contemporary datasets
Machine learning for application layer intrusion detection
Accelerating reliable multiscale quantum refinement of protein–drug systems enabled by machine learning
Machine Learning for Improving Surface-Layer-Flux Estimates
Efficient inverse design optimization through multi-fidelity simulations, machine learning, and boundary refinement strategies
Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations
Machine learning of surface layer property prediction for milling operations
Example-based decomposition, generalization and refinement for machine translation
Opening the machine learning black box with Layer-wise Relevance Propagation
On the estimation of boundary layer heights: a machine learning approach
Flow Characteristics of Fibrous Gas Diffusion Layers Using Machine Learning Methods
On the estimation of boundary layer heights: A machine learning approach
Validation and refinement of cropland map in southwestern China by harnessing ten contemporary datasets
Machine learning for application layer intrusion detection
Accelerating reliable multiscale quantum refinement of protein–drug systems enabled by machine learning
Machine Learning for Improving Surface-Layer-Flux Estimates
Efficient inverse design optimization through multi-fidelity simulations, machine learning, and boundary refinement strategies
Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations
Machine learning of surface layer property prediction for milling operations
Example-based decomposition, generalization and refinement for machine translation
Opening the machine learning black box with Layer-wise Relevance Propagation
On the estimation of boundary layer heights: a machine learning approach
Flow Characteristics of Fibrous Gas Diffusion Layers Using Machine Learning Methods