Pustovit, YuriyYuriyPustovitOhloblia, MaksymMaksymOhloblia2026-06-242026-06-242026-06-16Pustovit, Y., Ohloblia, M. (2026). Generated Training Dataset for Semantic Segmentation of ARPES Spectra [Data set]. https://doi.org/10.5281/zenodo.2072120910.5281/zenodo.20721209https://doi.org/10.5281/zenodo.20721209https://ir.library.knu.ua/handle/15071834/24960The dataset contains 11,000 generated ARPES spectral images (x_train and x_val, ) along with their corresponding ground truth segmentation masks ( y_train andy_val). The data is provided in HDF5 (.h5) format. Data Access & Code: The simulation code used to generate this dataset is publicly available at link. The dataset is partitioned into a training set and a validation set: Training set: 10,000 samples (x_train, y_train). intended for model training. Validation set: 1,000 samples (x_val, y_val) intended for evaluating model performance. The input spectra have a shape of (128,128,1), while the corresponding segmentation masks have a shape of (128,128,2). This specific dimensionality was chosen to ensure compatibility with U-Net architecture, which requires input dimensions to be powers of two (e.g., 128×128).  This dataset was used to train and evaluate the models proposed in: Pustovit, Yu. V., & Ohloblia, M. O. (2026). Semantic segmentation of ARPES spectra for electronic dispersion visualization. Low Temperature Physics, 52(2), 161–168. https://doi.org/10.1063/10.0042266ukdataset