All Outputs (3)

Applying machine learning to optical metrology: a review (2024)
Journal Article
Xue, R., Hooshmand, H., Isa, M., Piano, S., & K Leach, R. (2024). Applying machine learning to optical metrology: a review. Measurement Science and Technology, 36(1), Article 012002. https://doi.org/10.1088/1361-6501/ad7878

This literature review investigates the integration of machine learning (ML) into optical metrology, unveiling enhancements in both efficiency and effectiveness of measurement processes. With a focus on phase demodulation, unwrapping, and phase-to-he... Read More about Applying machine learning to optical metrology: a review.

Machine learning-based envelope extraction from downsampled coherence scanning interferometry signal data (2024)
Presentation / Conference Contribution
Xue, R., Hooshmand, H., Isa, M., & Leach, R. (2024, September). Machine learning-based envelope extraction from downsampled coherence scanning interferometry signal data. Presented at Special Interest Conference: Structured & Freeform Surfaces, Nottingham, UK

An Indexable Time Series Dimensionality Reduction Method for Maximum Deviation Reduction and Similarity Search (2022)
Presentation / Conference Contribution
Xue, R., Yu, W., & Wang, H. (2022, March). An Indexable Time Series Dimensionality Reduction Method for Maximum Deviation Reduction and Similarity Search. Presented at International Conference on Extending Database Technology (ACM EDBT'22)), Edinburgh, UK and online

Similarity search over time series is essential in many applications. However, it may cause “the curse of dimensionality” due to the high dimensionality of time series. Various dimensionality reduction methods have been developed. Some of them sacrif... Read More about An Indexable Time Series Dimensionality Reduction Method for Maximum Deviation Reduction and Similarity Search.