Communication Dans Un Congrès Année : 2021

On the value of CTIS imagery for neural network based classification : experimental results

Résumé

The computed tomography imaging spectrometer (CTIS) is a snapshot hyper-spectral imaging system which has recently been demonstrated of value when used in a compressed learning mode. In such a mode, the raw data are not reconstructed in an hyperspectral cube but are directly transmitted to a neural network to perform classification. While the previous investigations on this topic were limited to a simulation perspective, we extend these results to real images and demonstrate the possibility to train the network on simulated data and apply this trained model successfully on real images.
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Dates et versions

hal-03248645 , version 1 (03-06-2021)

Identifiants

  • HAL Id : hal-03248645 , version 1

Citer

Clément Douarre, Carlos F Crispim-Junior, Anthony Gélibert, Laure Tougne, David Rousseau. On the value of CTIS imagery for neural network based classification : experimental results. OSA Imaging and Applied Optics Congress, Jul 2021, Washington, DC,, United States. ⟨hal-03248645⟩
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