SPMS 2025

Session

Machine Learning Applications and Data Analysis

Jun 20, 2025, 10:30 AM

Conveners

Machine Learning Applications and Data Analysis

• Jiří Franc (Czech Technical University (CZ))

Machine Learning Applications and Data Analysis

• František Gašpar (FJFI)

17. Reconstruction of Powder Diffractograms in 4D-STEM Microscopy

David Rendl

6/20/25, 10:40 AM

This presentation addresses the reconstruction of 2D powder diffractograms acquired using 4D-STEM in SEM microscopy. Using image processing techniques, we aim to improve the analysis of crystalline samples through a novel method, 4D-STEM/PNBD, developed in collaboration with UMCH and UTIA. After a brief introduction to the 4D-STEM/PNBD framework, we summarize existing reconstruction approaches...

15. Subgroup detection using embedding-based approaches

Matyáš Veselý

6/20/25, 11:05 AM

We present SDUEBA, a structured and modular pipeline for subgroup discovery that combines embedding-based instance representation, manifold-space clustering, and interpretable rule induction using decision trees. Designed to overcome the limitations of traditional exhaustive search methods, SDUEBA transforms heterogeneous input data—including categorical, numerical, binary, and textual...

10. Explainability in Deep Learning using AJIVE matrix factorization

Jan Zavadil (UiT)

6/20/25, 11:30 AM

This contribution presents results of an ongoing project on explainable AI in context of breast cancer risk prediction. The problem is addressed as a multi-view classification task on x-ray mammography images. The two views of a standard mammography screening (CC and MLO) are considered as distinct modalities and a CNN based deep neural network is used to predict the cancer risk score...

9. Estimation of source term of Chernobyl wildfires using variational deep image prior

Antonie Brožová

6/22/25, 9:20 AM

In April 2020, monitoring stations across Europe detected the presence of Cesium-137, released during wildfires in the Chernobyl region. The source of this emission is believed to be both spatially and temporally distributed, with Cesium-137 bound to particles of varying sizes. To estimate the spatio-temporal distribution of the emission, we formulate the task as an inverse problem using a...

8. SpheroSeg: A platform for robust segmentation of tumor spheroids

Michal Průšek

6/22/25, 9:45 AM

Accurate quantitative analysis of 3D multicellular tumor spheroids is crucial in cancer research and drug development. However, manual segmentation of machine-scanned data is time-consuming and represents a significant obstacle to further development in this field. This presentation introduces SpheroSeg, a new AI-based web platform for robust spheroid segmentation. We will describe the process...