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CFFormer: Channel Fourier Transformer for Remote Sensing Super Resolution
Published 2025-01-01Get full text
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3227
A Synergistic CNN-DF Method for Landslide Susceptibility Assessment
Published 2025-01-01“…The complex structures and intricate hyperparameters of existing deep learning (DL) models make achieving higher accuracy in landslide susceptibility assessment (LSA) time-consuming and labor-intensive. …”
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Satellite-Derived Bathymetry Combined With Sentinel-2 and ICESat-2 Datasets Using Deep Learning
Published 2025-01-01Get full text
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3229
Multiclass Crop Interpretation via a Lightweight Attentive Feature Fusion Network Using Vehicle-View Images
Published 2025-01-01Get full text
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Refinement Analysis of Real Dihedral and Trihedral CR-InSAR Based on TerraSAR-X and Sentinel-1A Images
Published 2024-01-01Get full text
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VTWSAR: A Fast Calculation Method for Visible Time Window of SAR Satellite to Regional Target
Published 2025-01-01Get full text
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Enhancing Aerosol Vertical Distribution Retrieval With Combined LSTM and Transformer Model From OCO-2 O2 A-Band Observations
Published 2025-01-01“…Furthermore, a physics-based, information-driven band selection method was developed to simplify input data and reduce complexity. …”
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TMAR: 3-D Transformer Network via Masked Autoencoder Regularization for Hyperspectral Sharpening
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SSL-MBC: Self-Supervised Learning With Multibranch Consistency for Few-Shot PolSAR Image Classification
Published 2025-01-01“…Nevertheless, fully utilizing SSL in PolSAR classification tasks is still a great challenge due to the data complexity. Based on the abovementioned issues, we propose an SSL model with multibranch consistency (SSL-MBC) for few-shot PolSAR image classification. …”
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Different Scale Crack Contour Extraction Techniques for Bridges Incorporating Improved YOLOv5 and GCNet
Published 2025-01-01“…Aiming at the lack of accuracy and efficiency of the traditional detection methods and the existing deep learning-based detection methods, this study proposes a contour extraction model for bridge cracks at different scales based on the deep learning algorithm. …”
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