Sato, RyoRyoSatoLi, XinghuiXinghuiLiFischer, AndreasAndreasFischerLIANG-CHIA CHENChen, ChongChongChenShimomura, RintaroRintaroShimomuraGao, WeiWeiGao2023-07-242023-07-242023-01-0122347593https://scholars.lib.ntu.edu.tw/handle/123456789/634130The confocal probe is one of the most well-used optical sensors for displacement/position measurement as well as for mapping of three-dimensional microstructured surfaces and internal structures. A dual-detection configuration employing two detectors is often used in the state-of-the-art confocal probes to achieve wider measurement ranges, higher resolutions, better accuracies and faster measurement speeds. In this paper, the motivation and benefits for development and employment of the dual-detection confocal probes, as well as the investigation of the detector positions, are first presented. The signal processing methods associated with the dual-detection confocal probes are then categorized into the difference-type and the ratio-type, followed by descriptions on the features of each method. Finally, signal processing based on artificial intelligence and machine learning for the confocal probes are presented.Artificial intelligence | Confocal microscopy | Difference | Dual-detection confocal probe | Machine learning | Off-focus | On-focus | Ratio | Signal processingother10.1007/s12541-023-00842-32-s2.0-85163362013https://api.elsevier.com/content/abstract/scopus_id/85163362013