Meta-imagers for machine vision

Hanyu Zheng; Brandon Swartz; Quan Liu; Xiaomeng Zhang; Ivan Kravchenko; Gregory Forcherio; Yuankai Huo; Jason G. Valentine

doi:10.1117/12.3002606

13 March 2024 Meta-imagers for machine vision

Hanyu Zheng, Brandon Swartz, Quan Liu, Xiaomeng Zhang, Ivan Kravchenko, Gregory Forcherio, Yuankai Huo, Jason G. Valentine

Author Affiliations +

Proceedings Volume PC12897, High Contrast Metastructures XIII; PC128970D (2024) https://doi.org/10.1117/12.3002606
Event: SPIE OPTO, 2024, San Francisco, California, United States

Abstract

We demonstrate meta-optic based accelerators that can off-load computationally expensive operations into high-speed and low-power optics. The key to these architectures are the new freedoms afforded by metasurfaces such as optical edge isolation, polarization discrimination, and the ability to spatially multiplex, and demultiplex, information channels. I will discuss how these freedoms can be utilized for accelerating optical segmentation networks and objection classifiers, both based on incoherent illumination. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine-vision and artificial intelligence.

Conference Presentation

Citation Download Citation

Hanyu Zheng, Brandon Swartz, Quan Liu, Xiaomeng Zhang, Ivan Kravchenko, Gregory Forcherio, Yuankai Huo, and Jason G. Valentine "Meta-imagers for machine vision", Proc. SPIE PC12897, High Contrast Metastructures XIII, PC128970D (13 March 2024); https://doi.org/10.1117/12.3002606

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