Muhammed Özgölet

An Interpretable Kolmogorov–Arnold Network for FTIR Detection and Quantification of Adulteration Across Diverse Food Matrices

Economically motivated adulteration of olive oil, coffee and fruit juice is a persistent food-fraud problem for which Fourier-transform infrared (FTIR) spectroscopy with chemometrics offers rapid screening. Linear partial least squares (PLS) is interpretable but cannot capture non-linear mixing; neural networks add fle...