https://scholars.lib.ntu.edu.tw/handle/123456789/634130
標題: | Signal Processing and Artificial Intelligence for Dual-Detection Confocal Probes | 作者: | Sato, Ryo Li, Xinghui Fischer, Andreas LIANG-CHIA CHEN Chen, Chong Shimomura, Rintaro Gao, Wei |
關鍵字: | Artificial intelligence | Confocal microscopy | Difference | Dual-detection confocal probe | Machine learning | Off-focus | On-focus | Ratio | Signal processing | 公開日期: | 1-一月-2023 | 來源出版物: | International Journal of Precision Engineering and Manufacturing | 摘要: | The 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. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/634130 | ISSN: | 22347593 | DOI: | 10.1007/s12541-023-00842-3 |
顯示於: | 機械工程學系 |
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