BENCHMARK OF MACHINE LEARNING METHODS FOR CLASSIFICATION OF A SENTINEL-2 IMAGE

13 citations as recorded by crossref.

1. Intelligent mapping of irrigated areas from Landsat 8 images using transfer learning Z. BENBAHRIA et al.
2. A New Application of Random Forest Algorithm to Estimate Coverage of Moss-Dominated Biological Soil Crusts in Semi-Arid Mu Us Sandy Land, China X. Chen et al.
3. Evaluation of the Potential of Convolutional Neural Networks and Random Forests for Multi-Class Segmentation of Sentinel-2 Imagery V. Syrris et al.
4. Open source R for applying machine learning to RPAS remote sensing images M. Piragnolo et al.
5. Land cover object change monitoring and environmental suitability confirmation in Cat Ba Biosphere Reserve of Vietnam L. Hue et al.
6. Developing a New Method to Rapidly Map Eucalyptus Distribution in Subtropical Regions Using Sentinel-2 Imagery C. Tang et al.
7. Sunflower crop yield prediction by advanced statistical modeling using satellite-derived vegetation indices and crop phenology K. Amankulova et al.
8. Land use land cover (LULC) degradation intensity analysis of Guinea savannah and mosaic Forest savannah zones in Ghana K. Dahan et al.
9. Comparing Sentinel-2 and Landsat 9 for land use and land cover mapping assessment in the north of Congo Republic: a case study in Sangha region L. Bill Donatien et al.
10. Sentinel-2 Images and Machine Learning as Tool for Monitoring of the Common Agricultural Policy: Calasparra Rice as a Case Study F. López-Andreu et al.
11. Benchmarking Machine Learning Models for Polymer Informatics: An Example of Glass Transition Temperature L. Tao et al.
12. Land Use/Land Cover Mapping Using Multitemporal Sentinel-2 Imagery and Four Classification Methods—A Case Study from Dak Nong, Vietnam H. Nguyen et al.
13. Thematic Classification of Ukrainian Texts, Difficulties of its Introductions K. Bobrovnyk et al.