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Found 5 papers, 2 papers with code
Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation
Hyperspectral imaging provides detailed information about the scanned objects, as it captures their spectral characteristics within a large number of wavelength bands.
Unsupervised Segmentation of Hyperspectral Images Using 3D Convolutional Autoencoders
Hyperspectral image analysis has become an important topic widely researched by the remote sensing community.
Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images
Deep learning has established the state of the art in multiple fields, including hyperspectral image analysis.
Hyperspectral Data Augmentation
Data augmentation is a popular technique which helps improve generalization capabilities of deep neural networks.
Validating Hyperspectral Image Segmentation
Hyperspectral satellite imaging attracts enormous research attention in the remote sensing community, hence automated approaches for precise segmentation of such imagery are being rapidly developed.
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