- Can Deep Convolutional Neural Networks Discover Meaningful Pattern Features?Publication without faculty affiliation
- Deep convolutional neural network-based segmentation and classification of difficult to define metastatic spinal lesions in 3D CT data2018 | First Faculty of Medicine
- Machine and human interpretable patient visualizations2022 | Faculty of Mathematics and Physics, First Faculty of Medicine
- A deep CNN model for anomaly detection and localization in wireless capsule endoscopy images2021 | Faculty of Medicine in Hradec Králové
- VIRET Tool Meets NasNet2019 | Faculty of Mathematics and Physics
- Product exploration based on latent visual attributes2017 | Faculty of Mathematics and Physics
- Fully Automatic CAD System for Segmentation and Classification of Spinal Metastatic Lesions in CT Data2019 | First Faculty of Medicine
- A comparison of lineup fairness in human and computer-made photo arrays of different ethnicitiesPublication without faculty affiliation
- A comparison of lineup fairness in human and computer-made photo arrays of different ethnicities2019 | Faculty of Mathematics and Physics, Faculty of Arts
- Interpretable functional specialization emerges in deep convolutional networks trained on brain signals2022 | Second Faculty of Medicine
- Towards augmented database schemes by discovery of latent visual attributes2019 | Faculty of Mathematics and Physics
- On Visualizations in the Role of Universal Data Representation2020 | Faculty of Mathematics and Physics
- Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding2018 | Second Faculty of Medicine
- Predicting Sex From EEG: Validity and Generalizability of Deep-Learning-Based Interpretable Classifier2020 | Publication without faculty affiliation
- Visualizations for universal deep-feature representations: survey and taxonomy2024 | Faculty of Mathematics and Physics