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awesome-multimodal-remote-sensing-classification
List of datasets, papers, and codes related to multimodal/multisource/multisensor remote sensing classification
https://github.com/likyoo/awesome-multimodal-remote-sensing-classification
- LCZ Data (Multispectral and SAR data)
- Hong et al.2020
- DFC2018 Dataset (Multispectral LiDAR and Hyperspectral Data)
- Saux et al. 2018
- MUUFL Gulfport (Hyperspectral and LiDAR Data)
- Du et al.2017
- Houston2013 (Hyperspectral and LiDAR Data)
- Debes et al.2014
- Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art
- Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model
- Fractional Gabor Convolutional Network for Multisource Remote Sensing Data Classification
- Multisource Remote Sensing Data Classification With Graph Fusion Network
- Deep Residual Network-based Fusion Framework for Hyperspectral and LiDAR Data - RNDFF-RNPMF)
- Feature Correlation Analysis of Two-Branch Convolutional Networks for Multi-Source Image Classification
- A Multi-Sensor Fusion Framework Based on Coupled Residual Convolutional Neural Networks
- Multilevel Structure Extraction-Based Multi-Sensor Data Fusion - Structure-Extraction-Based-Multi-Sensor-Data-Fusion)
- SSR-NET: Spatial–Spectral Reconstruction Network for Hyperspectral and Multispectral Image Fusion
- More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification - RS)
- Joint Classification of Hyperspectral and LiDAR Data Using Hierarchical Random Walk and Deep CNN Architecture
- Learning-Shared Cross-Modality Representation Using Multispectral-LiDAR and Hyperspectral Data
- Deep Encoder-Decoder Networks for Classification of Hyperspectral and LiDAR Data
- Classification of Hyperspectral and LiDAR Data Using Coupled CNNs - CNNs)
- FusAtNet: Dual Attention based SpectroSpatial Multimodal Fusion Network for Hyperspectral and LiDAR Classification
- Feature Extraction for Classification of Hyperspectral and LiDAR Data Using Patch-to-Patch CNN
- Multi-Source Remote Sensing Data Classification via Fully Convolutional Networks and Post-Classification Processing
- Multisource Remote Sensing Data Classification Based on Convolutional Neural Network - branch-CNN-Multisource-RS-classification)
- Deep Fusion of Remote Sensing Data for Accurate Classification
- Inverse Coefficient of Variation Feature and Multilevel Fusion Technique for Hyperspectral and LiDAR Data Classification
- Combining feature fusion and decision fusion for classification of hyperspectral and LiDAR data
- pliang279/awesome-multimodal-ml
- Eurus-Holmes/Awesome-Multimodal-Research