Coding Convolutional Neural Networks as Spectral Transmittance for Intelligent Hyperspectral Remote Sensing in a Snapshot
| Autor: | Wenbin Xu, Shuo Chen, Liwa Wei, Xiaoyu Cui, Fengdi Zhang, Zhuoyu Zhang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry Remote sensing application Computer Science::Neural and Evolutionary Computation Hyperspectral imaging Spectral transmittance Geotechnical Engineering and Engineering Geology Convolutional neural network Data acquisition Computer Science::Computer Vision and Pattern Recognition Snapshot (computer storage) Computer vision Artificial intelligence Electrical and Electronic Engineering Optical filter business Computer Science::Databases Coding (social sciences) |
| Zdroj: | IEEE Geoscience and Remote Sensing Letters. 18:1635-1639 |
| ISSN: | 1558-0571 1545-598X |
| Popis: | The principle and procedure of coding a convolutional neural network (CNN) in terms of the spectral transmittance of a programmable optical filter are proposed and discussed. They exhibit an intrinsic link between the CNNs and the optical filters, which leads to a methodology by which optical imaging through such spectral transmittance can be seen as equivalent to the results of hyperspectral data numerically postprocessed by the CNN. In such a manner, hyperspectral data acquisition and CNN postprocessing can be implemented simultaneously by the physical process of optical imaging in a snapshot; thus, more intelligent, informative, and real-time optical detection and sensing in the remote sensing applications can be achieved. |
| Databáze: | OpenAIRE |
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