BENCHMARKING DEEP LEARNING FRAMEWORKS FOR THE CLASSIFICATION OF VERY HIGH RESOLUTION SATELLITE MULTISPECTRAL DATA

10 citations as recorded by crossref.

1. Detailed Land Cover Mapping from Multitemporal Landsat-8 Data of Different Cloud Cover C. Karakizi et al. 10.3390/rs10081214
2. Ontologies to interpret remote sensing images: why do we need them? D. Arvor et al. 10.1080/15481603.2019.1587890
3. Customer Visual Perception of Indoor Environments: Computer Vision Analysis of Social Media Photos of Cafés in China J. Dong & L. Li 10.1080/01490400.2022.2123873
4. Comparative Research on Deep Learning Approaches for Airplane Detection from Very High-Resolution Satellite Images U. Alganci et al. 10.3390/rs12030458
5. Multiplicative Long Short-Term Memory with Improved Mayfly Optimization for LULC Classification A. Stateczny et al. 10.3390/rs14194837
6. A Review of Deep Learning in Multiscale Agricultural Sensing D. Wang et al. 10.3390/rs14030559
7. A Patch-Level Data Synthesis Pipeline Enhances Species-Level Crop and Weed Segmentation in Natural Agricultural Scenes T. Li et al. 10.3390/agriculture15020138
8. Automatic Gully Detection: Neural Networks and Computer Vision A. Gafurov & O. Yermolayev 10.3390/rs12111743
9. Land-Use and Land-Cover Classification Using a Human Group-Based Particle Swarm Optimization Algorithm with an LSTM Classifier on Hybrid Pre-Processing Remote-Sensing Images G. Rajendran et al. 10.3390/rs12244135
10. Satellite data cloud detection using deep learning supported by hyperspectral data L. Sun et al. 10.1080/01431161.2019.1667548