Home ›
Entities
› academia
› A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions
A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions
Research article (Remote Sensing, 2020) · cited 45× · AI/ML
A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions
Summary
A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions is a scholarly article[1].
Key Facts
A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-hybrid-data-balancing-method-for-classification-of-imbalanced-training-data-within-google-earth-engine-case-studies-fr
MLA“A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-hybrid-data-balancing-method-for-classification-of-imbalanced-training-data-within-google-earth-engine-case-studies-fr.
BibTeX@misc{4ortxyz_a-hybrid-data-balancing-method-for-classification-of-imbalanced-training-data-within-google-earth-engine-case-studies-fr_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions}}, year = {2026}, url = {https://4ort.xyz/entity/a-hybrid-data-balancing-method-for-classification-of-imbalanced-training-data-within-google-earth-engine-case-studies-fr}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A Hybrid Data Balancing Method for Classification of Imbalanced Training Data within Google Earth Engine: Case Studies from Mountainous Regions — https://4ort.xyz/entity/a-hybrid-data-balancing-method-for-classification-of-imbalanced-training-data-within-google-earth-engine-case-studies-fr (retrieved 2026-05-24)
