Wenhao Tang 1†Qing Yang 1,2,3Hang Xu 1Yiyu Guo 1[ ... ]Xu Liu 2,3,*
Author Affiliations
Abstract
1 Zhejiang Laboratory, Research Center for Frontier Fundamental Studies, Hangzhou, China
2 Zhejiang University, College of Optical Science and Engineering, State Key Laboratory of Extreme Photonics and Instrumentation, Hangzhou, China
3 ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, China
4 Shanghai Jiao Tong University, Chip Hub for Integrated Photonics Xplore (CHIPX), Wuxi, China
With the rapid development of sensor networks, machine vision faces the problem of storing and computing massive data. The human visual system has a very efficient information sense and computation ability, which has enlightening significance for solving the above problems in machine vision. This review aims to comprehensively summarize the latest advances in bio-inspired image sensors that can be used to improve machine-vision processing efficiency. After briefly introducing the research background, the relevant mechanisms of visual information processing in human visual systems are briefly discussed, including layer-by-layer processing, sparse coding, and neural adaptation. Subsequently, the cases and performance of image sensors corresponding to various bio-inspired mechanisms are introduced. Finally, the challenges and perspectives of implementing bio-inspired image sensors for efficient machine vision are discussed.
bio-inspired image sensor machine vision layer-by-layer processing sparse coding neural adaptation 
Advanced Photonics
2024, 6(2): 024001
作者单位
摘要
北京理工大学 光电学院 “复杂环境智能感测技术”工信部重点实验室, 北京 100081
熔融石英玻璃因具有耐热性高、热膨胀系数低、绝缘性能好等优点, 广泛应用于航空航天、微光学元件、**等领域, 并对其加工精度和表面质量提出了更高的要求。由于飞秒激光具有“冷加工”的特点, 因此在熔融石英玻璃微纳加工方面展现出独特优势。采用波长为1030nm、重复频率为100kHz、脉宽为290fs的飞秒激光对熔融石英玻璃进行加工, 确定了不同物镜下熔融石英玻璃的损伤阈值, 研究了不同物镜下的激光功率、扫描速度、离焦量、扫描次数对加工线槽的影响, 使用逐层叠加加工的方法在低功率下得到了高深宽比(4∶1)的线槽, 并且提高加工线槽的宽度与深度的可控性, 可以在较薄熔融石英玻璃(200μm)上进行微纳加工。
激光技术 熔融石英玻璃 飞秒激光 微纳加工 损伤阈值 逐层叠加加工 laser techniques fused silica glass femtosecond laser micronano machining damage threshold layer by layer processing 
光学技术
2023, 49(6): 664

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