Ing.

Štěpán Ježek

FEKT, UTKO – vědecký pracovník

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xjezek16@vut.cz

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Ing. Štěpán Ježek

Publikační výsledky

  • 2025

    TYAGI, N.; JOSHI, R.; DAS, S.; KUNAL, .; SCHILLER, V.; JEŽEK, Š.; DUTTA, M. Multi-Domain Information-Theoretic Features and Kolmogorov Complexity for Lightweight Image Splicing Detection. 2025 17th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE, 2025. p. 227.

    Stať ve sborníku mimo WoS a Scopus

    Detail

    MYŠKA, V.; BURGET, R.; JEŽEK, Š.; LUŇÁKOVÁ, M.; MORAVCOVÁ, P.; DOUBKOVÁ, Š.; MEZINA, A.; JONÁK, M. Writer Identification Using Siamese Networks and Character-Level Analysis. In 2025 17th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). Italy: IEEE, 2025. p. 182-186. ISBN: 979-8-3315-7675-2.

    Stať ve sborníku v databázi WoS či Scopus

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    LUŇÁKOVÁ, M.; DORAZIL, J.; JONÁK, M.; JEŽEK, Š.; BURGET, R. Pen Ink Library: An interactive database of writing instruments based on Vis-NIR reflection spectra and optical properties of inks. Forensic Science International, 2025, vol. 373, iss. Srpen, p. 1-13. ISSN: 1872-6283.

    Článek WoS

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    JEŽEK, Š.; KŘÍŽ, P.; ŘÍHA, K.; BURGET, R.; DUSÍK, M. Automatic Traffic Camera Calibration Using 3D Scene Reconstruction with Structure-from-Motion and Custom Image Data. In ICUMT 2024; 16th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops. International Congress on Ultra Modern Telecommunications and Workshops. 2025. p. 19-24. ISBN: 978-3-8007-6544-7.

    Stať ve sborníku v databázi WoS či Scopus

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    JEŽEK, Š.; BURGET, R. Speed Measurement from Traffic Camera Video Using Structure-from-Motion-Based Calibration. In Proceedings II of the 31th Student EEICT 2025: Selected Papers. Proceedings II of the Conference STUDENT EEICT. Brno: Brno University of Technology, Faculty of Electronic Engineering and Communication, 2025. p. 246-250. ISBN: 978-80-214-6320-2.

    Stať ve sborníku v databázi WoS či Scopus

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  • 2024

    JEŽEK, Š.; BURGET, R. Deployment of deep learning-based anomaly detection systems: challenges and solutions. In Proceedings II of the 30th Student EEICT 2024: Selected Papers. Proceedings II of the Conference STUDENT EEICT. 1. Brno: Brno University of Technology, Faculty of Electronic Engineering and Communication, 2024. p. 207-211. ISBN: 978-80-214-6230-4. ISSN: 2788-1334.

    Stať ve sborníku v databázi WoS či Scopus

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    JONÁK, M.; MUCHA, J.; JEŽEK, Š.; KOVÁČ, D.; CZÍRIA, K. SPAGRI-AI: Smart precision agriculture dataset of aerial images at different heights for crop and weed detection using super-resolution. AGRICULTURAL SYSTEMS, 2024, vol. 216, iss. April 2024, p. 1-11. ISSN: 0308-521X.

    Článek WoS

    Detail

    NANDI, T.; GUPTA, S.; KAUSHAL, A.; DUTTA, M.; BURGET, R.; JEŽEK, Š. Semantic Fusion of Text and Images: A Novel Multimodal-RAG Framework for Document Analysis. In ICUMT 2024; 16th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops. International Congress on Ultra Modern Telecommunications and Workshops. Meloneras: 2024. p. 106-110. ISBN: 978-3-8007-6544-7.

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  • 2023

    JONÁK, M.; DORAZIL, J.; KOLAŘÍK, M.; JEŽEK, Š.; BURGET, R.; KOTRLÝ, M. Forensic Comparison of Soil Particles Using Gaussian Mixture Models and Likelihood Ratio Test. In 2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE Computer Society, 2023. p. 188-192. ISBN: 979-8-3503-9328-6.

    Stať ve sborníku v databázi WoS či Scopus

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    JEŽEK, Š.; BURGET, R.; VERMA, S.; VISHAL, V.; JOSHI, R.; DUTTA, M. AI-enhanced Mental Health Diagnosis: Leveraging Transformers for Early Detection of Depression Tendency in Textual Data. In 2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE Computer Society, 2023. p. 56-61. ISBN: 979-8-3503-9328-6.

    Stať ve sborníku v databázi WoS či Scopus

    Detail

    JEŽEK, Š. Visual defect detection in real-world industrial applications using convolutional neural networks. Proceedings I of the 29th Student EEICT 2023 (General Papers). Brno: 2023. p. 389.ISBN: 978-80-214-6153-6.

    Stať ve sborníku mimo WoS a Scopus

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  • 2022

    JONÁK, M.; JEŽEK, Š.; BURGET, R. Evaluation of Nested U-Net models performance on MVTec AD dataset. In 2022 14th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). Valencia, Spain: IEEE, 2022. p. 70-75. ISBN: 979-8-3503-9866-3.

    Stať ve sborníku v databázi WoS či Scopus

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    JEŽEK, Š.; JONÁK, M.; BURGET, R.; DVOŘÁK, P.; SKOTÁK, M. Anomaly detection for real-world industrial applications: benchmarking recent self-supervised and pretrained methods. In 2022 14th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). Valencia, Spain: IEEE, 2022. p. 64-69. ISBN: 979-8-3503-9866-3.

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  • 2021

    JEŽEK, Š.; JONÁK, M.; BURGET, R.; DVOŘÁK, P.; SKOTÁK, M. Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions. In 2021 13th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). Online: IEEE, 2021. p. 66-71. ISBN: 978-1-6654-0219-4.

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*) Citace se generují jednou za 24 hodin.