Výsledky vyhledávání - "Reinikainen, Satu

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Kernel-based retrieval models for hyperspectral image data optimized with Kernel Flows

Autor: Duma, Zina-Sabrina, Sihvonen, Tuomas, Susiluoto, Jouni, Lamminpää, Otto, Haario, Heikki, Reinikainen, Satu-Pia

Kernel-based statistical methods are efficient, but their performance depends heavily on the selection of kernel parameters. In literature, the optimization studies on kernel-based chemometric methods is limited and often reduced to grid searching. P

Externí odkaz: http://arxiv.org/abs/2411.07800

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Statistical Batch-Based Bearing Fault Detection

Autor: Jorry, Victoria, Duma, Zina-Sabrina, Sihvonen, Tuomas, Reinikainen, Satu-Pia, Roininen, Lassi

In the domain of rotating machinery, bearings are vulnerable to different mechanical faults, including ball, inner, and outer race faults. Various techniques can be used in condition-based monitoring, from classical signal analysis to deep learning m

Externí odkaz: http://arxiv.org/abs/2407.17236

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Varroa destructor detection on honey bees using hyperspectral imagery

Autor: Duma, Zina-Sabrina, Zemcik, Tomas, Bilik, Simon, Sihvonen, Tuomas, Honec, Peter, Reinikainen, Satu-Pia, Horak, Karel

Hyperspectral (HS) imagery in agriculture is becoming increasingly common. These images have the advantage of higher spectral resolution. Advanced spectral processing techniques are required to unlock the information potential in these HS images. The

Externí odkaz: http://arxiv.org/abs/2403.14359

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KF-PLS: Optimizing Kernel Partial Least-Squares (K-PLS) with Kernel Flows

Autor: Duma, Zina-Sabrina, Susiluoto, Jouni, Lamminpää, Otto, Sihvonen, Tuomas, Reinikainen, Satu-Pia, Haario, Heikki

Partial Least-Squares (PLS) Regression is a widely used tool in chemometrics for performing multivariate regression. PLS is a bi-linear method that has a limited capacity of modelling non-linear relations between the predictor variables and the respo

Externí odkaz: http://arxiv.org/abs/2312.06547

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