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Fall 2019
Data-driven approaches have been profoundly studied and successfully applied for process industries, such as in the development of inferential sensors. Among a variety of modelling techniques, the latent variable modelling approaches are widely preferred, which can learn informative features from...
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Pattern Recognition of Time-dependent Cellular Response of Chemicals Based on Profile Shape Similarity
DownloadSpring 2014
As a potential approach to interpret Mode of Action (MoA), the shape of cellular response profiles associated with chemicals has been a key consideration. In this thesis, statistical pattern recognition methods using multiconcentration time-dependent cellular response profiles (TCRPs) are...
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2004
Technical report TR04-10. This report overviews the Mass Spectrometry Data Classification and Feature Extraction problem. After reviewing previous research new classification and feature extraction techniques are presented and empirically evaluated on three data sets. One of the key points made...
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Scalable Solutions to Image Abnormality Detection and Restoration using Limited Contextual Information
DownloadFall 2020
Detecting and interpreting image abnormalities and restoring images are essential to many processing pipelines in diverse fields. Challenges involved include randomness and unstructured nature of image artefacts (from signal processing perspective) and performance constraints imposed by...