Session Index

Holography and Information Processing

Holography and Information Processing III
Friday, Dec. 4, 2020  13:10-15:40
Presider: Prof. Yuan Luo
Prof. Jing-Heng Chen
Room: 6AB Room 327
Notes:
13:10 - 13:40 Manuscript ID.  0817
Paper No.  2020-FRI-S0403-I001
Invited Speaker:
Sarun Sumriddetchkajorn

Conceptual Architecture of 3D Photonic Convolution Neural Network using Off-the-Shelf Devices
Sarun Sumriddetchkajorn

This paper proposes a conceptual design for hybrid optical-electronic convolution neural network. The key design exploits the inherent advantage of 3D photonics architecture that provides inversion, multiplication, and summation of the images. This concept can be made possible by using today smart phones or tablets and high-definition liquid crystal displays.

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13:40 - 14:10 Manuscript ID.  0801
Paper No.  2020-FRI-S0403-I002
Invited Speaker:
Chung-Hao Tien

Deep learning for computational optics
Chung-Hao Tien

Computation resources and machine learning have made a rapid progress in the last decade. Inspired by the computer science community focusing on data interpretation, computational optics took further step to investigate more possibility about the image formation. In this study, I will present some data-driven works including image denoising, phase retrieval and unconventional imaging system based on deep learning neural network.

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14:10 - 14:40 Manuscript ID.  0464
Paper No.  2020-FRI-S0403-I003
Invited Speaker:
Jing-Heng Chen

Design and Fabrication of Polarization-selective Substrate-mode Volume Holograms
Jing-Heng Chen;Fan-Hsi Hsu;Chien-Yuan Han;Kun-Huang Chen;Chien-Hung Yeh;Ken-Yuh Hsu

A prism-hologram-prism sandwiched recording method is proposed for the fabrication of polarization-selective substrate-mode volume holograms with a large diffraction angle. The method belongs to a technique of longer-wavelength construction for shorterwavelength reconstruction and is much easier than that of traditional method which has high application potential in holographic photonics.

 
 
14:40 - 14:55 Manuscript ID.  0549
Paper No.  2020-FRI-S0403-O001
Vinoth Balasubramani
Deep Learning-enabled Particle Detection and Sorting in Three-Dimensions with Digital Holography
Vinoth Balasubramani;Yang-Jie Gao;Chung-Hsuan Huang;Li-Chien Lin;Chau-Jern Cheng

A novel deep learning model for particle detection and sorting in three-dimensions with digital holography was proposed and demonstrated. Deep learning models such as U-net and convolution neural network are implemented to predict and estimate the particle’s size and its orientations in lateral and axial directions.

 
 
14:55 - 15:10 Manuscript ID.  0009
Paper No.  2020-FRI-S0403-O002
JING-FENG WENG
Three Dimensional Profile Algorithm based on the Number of Interference Slope Fluctuations without Phase Unwrapping
JING-FENG WENG;GUO-HAO LU;CHUN-JEN WENG;YU-HSIN LIN;ChAO-FENG LIU;ROBBIE VINCKE;HSIAO-CHUN TING;TING-TING CHANG

In this study, the presented novel algorithm, based on the interferometry techniques, is used to rebuild the profile of the step height sample and the dirty position. By contrast, the phase unwrapping algorithm and the zero-order interference fringe fail to simultaneously rebuild the profile of sample and the dirty position.

 
 
15:10 - 15:25 Manuscript ID.  0131
Paper No.  2020-FRI-S0403-O003
Yen-Chung Wang
Image stitching by using algorithm of frequency domain signal similarity
Yen-Chung Wang;JING-FENG WENG;GUO-HAO LU;ChAO-FENG LIU;CHUN-JEN WENG;Pi-Ying Cheng

This study presents the algorithm to distinguish the strong and signals, and the noise in the input of three images. All of the detected strong signal (or weak signal) can combine to the one stitching image. By contrast, the known Speeded Up Robust Features does not effectively distinguish these signals.