DATA AUGMENTATION APPROACHES FOR SATELLITE IMAGE SUPER-RESOLUTION

9 citations as recorded by crossref.

1. MBAHIL: Design of a Multimodal Hybrid Bioinspired Model for Augmentation of Hyperspectral Imagery via Iterative Learning for Continuous Efficiency Enhancements D. Saini et al. 10.1109/ACCESS.2023.3273529
2. Spatial Super Resolution of Real-World Aerial Images for Image-Based Plant Phenotyping M. Aslahishahri et al. 10.3390/rs13122308
3. Application of a generative adversarial network for multi-featured fermentation data synthesis and artificial neural network (ANN) modeling of bitter gourd–grape beverage production S. Gbashi et al. 10.1038/s41598-023-38322-3
4. PlanetScope Radiometric Normalization and Sentinel-2 Super-Resolution (2.5 m): A Straightforward Spectral-Spatial Fusion of Multi-Satellite Multi-Sensor Images Using Residual Convolutional Neural Networks N. Latte & P. Lejeune 10.3390/rs12152366
5. Super-Resolution of Sentinel-2 Images Using a Spectral Attention Mechanism M. Zabalza & A. Bernardini 10.3390/rs14122890
6. A review on remote sensing imagery augmentation using deep learning V. Lalitha & B. Latha 10.1016/j.matpr.2022.03.341
7. Socio-environmental land cover time-series analysis of mining landscapes using Google Earth Engine and web-based mapping M. Ang et al. 10.1016/j.rsase.2020.100458
8. A Deep Learning Model for Wafer Defect Map Classification: Perspective on Classification Performance and Computational Volume M. Kim et al. 10.1002/pssb.202300113
9. PatchMask: A Data Augmentation Strategy with Gaussian Noise in Hyperspectral Images H. Dou et al. 10.3390/rs14246308