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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Advanced Materialsarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Advanced Materials
Article . 2022 . Peer-reviewed
License: Wiley Online Library User Agreement
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A Meta‐Device for Intelligent Depth Perception

Authors: Mu Ku Chen; Xiaoyuan Liu; Yongfeng Wu; Jingcheng Zhang; Jiaqi Yuan; Zhengnan Zhang; Din Ping Tsai;

A Meta‐Device for Intelligent Depth Perception

Abstract

AbstractThe optical illusion affects depth‐sensing due to the limited and specific light‐field information acquired by single‐lens imaging. The incomplete depth information or visual deception would cause cognitive errors. To resolve this problem, an intelligent and compact depth‐sensing meta‐device that is miniaturized, integrated, and applicable for diverse scenes in all light levels is demonstrated. The compact and multifunction stereo vision system adopts an array with 3600 achromatic meta‐lenses and a size of 1.2 × 1.2 mm2 to measure the depth over a 30 cm range with deep‐learning support. The meta‐lens array can act as multiple imaging lenses to collect light field information. It can also work with a light source as an active optical device to project a structured light. The meta‐lens array can serve as the core functional component of a light‐field imaging system under bright conditions or a structured‐light projection system in the dark. The depth information in both ways can be analyzed and extracted by the convolutional neural network. This work provides a new avenue for the applications such as autonomous driving, machine vision, human–computer interaction, augmented reality, biometric identification, etc.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
107
Top 1%
Top 10%
Top 1%
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