Molecular information contained in bodily fluids (ex. Blood, urine, saliva, or tears) can be
minutely obtained through label-free surface-enhanced Raman spectroscopy (SERS) …

In recent years, machine learning (ML) has gained significant importance in the field of
cultural heritage research. Its advanced data analysis techniques have become a crucial …

Marine microplastics are emerging as a growing environmental concern due to their
potential harm to marine biota. The substantial variations in their physical and chemical …

Chemical agents are one of the major threats to soldiers in modern warfare, so it is so
important to detect chemical agents rapidly and accurately on battlefields. Raman …

Feature selection of high-dimensional labeled data with limited observations is critical for
making powerful predictive modeling accessible, scalable, and interpretable for domain …

Machine learning-assisted spectroscopy analysis faces a prominent constraint in the form of
insufficient spectral samples, which hinders its effectiveness. Meanwhile, there is a lack of …

Raman spectroscopy is a powerful tool for identifying substances, yet accurately analyzing
mixtures remains challenging due to overlap** spectra. This study aimed to develop a …

Deep learning has become the prevailing method for qualitative analysis of Raman
spectroscopy. However, for researchers and engineers without a background in computer …

Imaging in the near-infrared is affected by a background signal coming from both the
terrestrial atmosphere and the instrument itself, which plays an important role in limiting the …

In this thesis, we evaluated the performance of two generative models, Conditional Tabular
Generative Adversarial Network (CTGAN) and Tabular Variational Autoencoder (TVAE) …