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home/Knowledge Base/CODES/Deep Learning/More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification

September 24, 2020

More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification
Danfeng Hong, Lianru Gao, Naoto Yokoya, Jing Yao, Jocelyn Chanussot, Qian Du and Bing Zhang

IEEE Transactions on Geoscience and Remote Sensing
year : 2020
DOI: 10.1109/TGRS.2020.3016820

codes : https://github.com/danfenghong/IEEE_TGRS_MDL-RS

Tags:classificationconvolutional neural networkscross-modalitydeep learningfeature learningfusionhyperspectralLiDARmultimodalMultispectralnetwork architectureremote sensingsynthetic aperture radar
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Categories
  • CODES
    • Change Detection
    • Classification of Hyperspectral Images
    • Classification of Remote Sensing Data
    • Data fusion: hyperspectral + Lidar
    • Data fusion: Hyperspectral + Multispectral
    • Deep Learning
    • Denoising
    • Graphs, Manifold
    • Hyperspectral
    • Hyperspectral remote sensing
    • Hyperspectral Super Resolution
    • Machine Learning in Remote Sensing
    • Multi-modal
    • Pansharpening
    • Registration
    • Sequences
    • Spectral Unmixing
    • Super Resolution
    • Synthetic Aperture Radar and Radar Sounder
    • Tensor
  • DATA
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