| Autor: |
Yunzhe Li, Shiyi Cheng, Yujia Xue, Lei Tian |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Emerging Topics in Artificial Intelligence (ETAI) 2021. |
| DOI: |
10.1117/12.2594043 |
| Popis: |
Imaging through scattering medium has wide applications across many areas. Here, we present a new deep learning framework for improving the robustness against physical perturbations of the scattering medium. The trained DNN can make high-quality predictions beyond the training range which is across 10X depth-of-field (DOF). We develop a new analysis framework based on dimensionality reduction for revealing the information contained in the speckle dataset, interpreting the mechanism of our DNN, and visualizing the generalizability of the DNN model. This allows us to further elucidate on the information encoded in both the raw speckle measurements and the working principle of our speckle-imaging deep learning model. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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