Conveners
Poster session + káva: prezentácie študentov informatika
- Kristina Malinovska (Department of Applied Informatics, FMPI CU)
- Martin Homola
- Robert Lukotka
Human--robot interaction requires robots whose actions are legible, allowing humans to interpret, predict, and feel safe around them. This study investigates the legibility of humanoid robot arm movements in a pointing task, aiming to understand how humans predict robot intentions from truncated movements and bodily cues. We designed an experiment using the NICO humanoid robot, where...
Space weathering impacts all objects exposed to the space environment, including artificial satellites and space debris. Exposure to high-energy solar particles, micrometeoroids, and atmospheric particles degrades surface materials through oxidation, erosion, and paint peeling, producing wavelength-dependent changes detectable with observations in Johnson-Cousins photometric bands.
These...
A Halin graph is a planar graph consisting of a tree and an additional cycle connecting all the leaves in such manner that no two edges are crossing.
Total colouring of a graph is a mapping from the set of vertices and edges to a set of colours such that no two neighbouring objects receive the same colour.
As there were only 4 known cubic Halin graphs with total chromatic index greater...
We continue the research of the notion of usefulness of information.
We formalize a problem by a regular language $L$ and we measure its complexity using the state complexity of the minimal automaton $A$ accepting the language $L$.
A language $L_{adv}$ provides a useful supplementary information about the problem, if it allows us to solve the problem easier, i.e., if it allows us to find an...
White matter hyperintensities (WMHs) or lesion in brain MRI are key biomarkers for neurological conditions, but detecting small lesions remains challenging. Existing deep learning models often act as “black boxes,” limiting clinical trust due to lack of interpretability. This study proposes a hybrid Xception-Vision Transformer (XViT) integrated with explainable AI (XAI) methods to enhance...
The state-of-the-art complete algorithms to solve ABox abduction in DL include the original Reiter’s algorithm for minimal hitting sets alongside its more recent updates: Wotawa’s HST and Pill and Quaritch’s RC-Tree. On the other hand, incomplete methods that quickly find some but not all solutions include Junker’s QuickXplain and MergeXplain by Shchekotykhin et al. We present CATS, a new...
Plasmids are small, circular, extrachromosomal DNA molecules commonly found in bacteria. They can be transferred between different bacterial cells through horizontal gene transfer and often carry genes conferring antimicrobial resistance (AMR), making them a critical focus in the study of antibiotic resistance.
The goal of our work is to develop new bioinformatics methods for plasmid...
We propose X-MalNet, an inherently explainable malware detection framework based on Matrix Product States (MPS) tensor networks. Unlike previous explainability methods that provide fragmented insights, X-MalNet natively generates multi-level explanations from a single coherent architecture. The MPS explicitly learns the joint probability distribution of features and labels, enabling faithful...
The preservation of historical documents is a crucial component of cultural heritage protection. One significant threat to these artifacts is the appearance of colored stains, which may originate from biological agents (e.g., fungi, bacteria, insects) or synthetic compounds (e.g., ink stamps, dyes). Currently, conservators rely primarily on subjective visual assessment and invasive analysis to...
A computer transmits visual information to a monitor as a continuous stream of RGB pixels, with their intensities encoded as voltage levels in the signal traveling through the video cable. The high-frequency voltage transitions of the signals generate unintentional electromagnetic emissions, which can be intercepted and used to reconstruct the displayed image. Under standard conditions, using...
In the age of AI becoming an everyday partner and support tool in both professional and private domains, users and stakeholders are increasingly confronted with the question of interpretability. This work contributes to the search for answers by exploring hidden meanings in the internal layers of convolutional neural networks trained on image classification tasks. Combining supervised...
We present a work-in-progress study on mitochondrial fluorescence microscopy scans using classical image-processing techniques. The workflow combines morphological and intensity-based segmentation with the extraction of descriptive textural features that capture structural variability of mitochondria. To identify the most informative characteristics, we apply systematic feature selection and...
