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We investigate a way to detect images of surface plasmon scattering using deep learning approach. Unlike fluorescence imaging, the image of surface plasmon scattering shows much worse resolution due to propagation length of surface plasmon polariton. In this work, deep learning approach is taken to address this issue and to discriminate multiple target objects under complex and noisy environment. Conventional detection method based on fourier filtering and deconvolution was employed to compare the performance of the proposed method. It was shown that deep learning improves the accuracy by about six times, and especially more useful in noisy environment.
Gwiyeong Moon,Taehwang Son,Hongki Lee, andDonghyun Kim
"Deep learning allows enhanced detection of surface plasmon scattering (Conference Presentation)", Proc. SPIE 11257, Plasmonics in Biology and Medicine XVII, 112570N (10 March 2020); https://doi.org/10.1117/12.2544169
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Gwiyeong Moon, Taehwang Son, Hongki Lee, Donghyun Kim, "Deep learning allows enhanced detection of surface plasmon scattering (Conference Presentation)," Proc. SPIE 11257, Plasmonics in Biology and Medicine XVII, 112570N (10 March 2020); https://doi.org/10.1117/12.2544169