dr inż. Michał Romaszewski

• Filus K.; Romaszewski M.; Żarski M.; Semantic Depth Matters: Explaining Errors of Deep Vision Networks through Perceived Class Similarities; Submitted: arXiv preprint

2026

• Kołodziej K.; Cholewa M.; Głomb P.; Koral W.; Romaszewski M.; Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials; ASCE Journal of Water Resources Planning and Management; 2026

2025

• Zawadzka A.; Żarski M.; Drejer K.; Głomb P.; Romaszewski M.; Cholewa M.; Map-Guided Cross-Training for Building Detection; Geoscience and Remote Sensing Letters; 2025
• Grochla K.; Romaszewski M.; Sotor J.; Masłowski P.; Belter B.; Towards AI-assisted Science with PLAI4SCIENCE - new Polish Research Infrastructure; 6th Polish Conference on Artificial Intelligence (PP-RAI 2025); 2025
• Cholewa M.; Romaszewski M.; Głomb P.; Data structure better than labels? Unsupervised heuristics for SVM hyperparameter estimation; Bulletin of the Polish Academy of Sciences Technical Sciences; 2025
• Książek K.; Masarczyk W.; Głomb P.; Romaszewski M.; Buza K.; Sekuła P.; Cholewa M.; Kołodziej K.; Gorczyca P.; Piegza M.; Deep learning approach for automatic assessment of schizophrenia and bipolar disorder in patients using R-R intervals; PLOS Computational Biology; 2025
• Gupta M.; Romaszewski M.; Gawron P.; Potential of quantum machine learning for processing multispectral Earth observation data; Bulletin of the Polish Academy of Sciences Technical Sciences; 2025
• Sekuła P.; Romaszewski M.; Głomb P.; Cholewa M.; Pawela Ł.; Quantum-aware Transformer model for state classification; International Conference on Computational Science 2025; 2025
• Romaszewski M.; Sekuła P.; Głomb P.; Cholewa M.; Kołodziej K.; Through the Thicket: A Study of Number-Oriented LLMS Derived from Random Forest Models; Journal of Artificial Intelligence and Soft Computing Research; 2025

2024

• Romaszewski M.; Sekuła P.; Poster: Explainable classification of multimodal time series using LLMs; 5th Polish Conference on Artificial Intelligence (PP-RAI 2024); 2024
• Kołodziej K.; Cholewa M.; Romaszewski M.; Głomb P.; Koral W.; Sekuła P.; Calibration of Water Demand Network Through a Machine Learned Digital Twin Model; 5th Polish Conference on Artificial Intelligence (PP-RAI 2024); 2024
• Kołodziej K.; Cholewa M.; Głomb P.; Koral W.; Romaszewski M.; Efficient Numerical Calibration of Water Delivery Network Using Short-Burst Hydrant Trials; arXiv preprint arXiv:2410.02772; 2024
• Cholewa M.; Romaszewski M.; Głomb P.; Kołodziej K.; Gorawski M.; Koral J.; Koral W.; Madej A.; Musioł K.; ‘Just One More Sensor is Enough’ – Iterative Water Leak Localization with Physical Simulation and a Small Number of Pressure Sensors; IEEE Sensors Journal; 2024
• Romaszewski M.; Sekuła P.; Głomb P.; Cholewa M.; Kołodziej K.; Through the Thicket: A Study of Number-Oriented LLMs derived from Random Forest Models; arXiv preprint arXiv:2406.04926; 2024
• Książek K.; Masarczyk W.; Głomb P.; Romaszewski M.; Stokłosa I.; Ścisło P.; Dębski P.; Pudlo R.; Buza K.; Gorczyca P.; Piegza M.; Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data; Computers in Biology and Medicine; 2024

2023

• Ciemięga A.; Maresz K.; Romaszewski M.; Głomb P.; Krupska-Wolas P.; Prusik K.; Hyperspectral Imaging as a Facile and Non-Destructive Method for Size Analysis of Gold Nanoparticles Deposited on Porous Materials; Particle & Particle Systems Characterization; 2023
• Książek K.; Masarczyk W.; Głomb P.; Romaszewski M.; Stokłosa I.; Ścisło P.; Dębski P.; Pudlo R.; Gorczyca P.; Piegza M.; HRV-ACC: a dataset with R-R intervals and accelerometer data for the diagnosis of psychotic disorders using a Polar H10 wearable sensor; 2023
• Książek K.; Masarczyk W.; Głomb P.; Romaszewski M.; Stokłosa I.; Ścisło P.; Dębski P.; Pudlo R.; Buza K.; Gorczyca P.; Piegza M.; The analysis of heart rate variability and accelerometer mobility data in the assessment of symptom severity in psychotic disorder patients using a wearable Polar H10 sensor; medXriv; 2023
• Głomb P.; Cholewa M.; Koral W.; Madej A.; Romaszewski M.; Detection of emergent leaks using machine learning approaches; Water Supply; 2023

2022

• Książek K.; Głomb P.; Romaszewski M.; Cholewa M.; Grabowski B.; Buza K.; Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation; 21st International Conference on Image Analysis and Processing; 2022

2021

• Pałka F.; Książek W.; Plawiak P.; Romaszewski M.; Książek K.; Hyperspectral Classification of Blood-Like Substances Using Machine Learning Methods Combined with Genetic Algorithms in Transductive and Inductive Scenarios; Sensors; 2021
• Romaszewski M.; Głomb P.; Sochan A.; Cholewa M.; A dataset for evaluating blood detection in hyperspectral images; Forensic Science International; 2021

2020

• Domino M.; Romaszewski M.; Jasiński T.; Maśko M.; Comparison of surface thermal patterns of horses and donkeys in IRT images [Data set]; 2020
• Romaszewski M.; Głomb P.; Sochan A.; Cholewa M.; A Dataset for Evaluating Blood Detection in Hyperspectral Images [Data set]; 2020
• Domino M.; Romaszewski M.; Jasiński T.; Maśko M.; Comparison of the Surface Thermal Patterns of Horses and Donkeys in Infrared Thermography Images; Animals; 2020