Search results for: UNSUPERVISED MACHINE LEARNING - Bridge of Knowledge

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Search results for: UNSUPERVISED MACHINE LEARNING

Best results in : Research Potential Pokaż wszystkie wyniki (96)

Search results for: UNSUPERVISED MACHINE LEARNING

  • Zespół Systemów Geoinformatycznych

    Research Potential

    W katedrze prowadzone są badania naukowe w zakresie szeroko rozumianych Systemów Informacji Geograficznej (GIS). Tematyka badań obejmuje zastosowanie GIS w technologiach bezpieczeństwa, wizualizacje i analizy przestrzenne, systemy numerycznego prognozowania pogody, technologie nawigacji w ramach mobilnych systemów informacji przestrzennej, oraz zaawansowane techniki obrazowania satelitarnego. Katedra kontynuuje również badania...

  • Zespół Systemów Multimedialnych

    * technologie archiwizacji, rekonstrukcji i dostępu do nagrań archiwalnych * technologie inteligentnego monitoringu wizyjnego i akustycznego * multimedialne technologie telemedyczne * multimodalne interfejsy komputerowe

  • Zespół Systemów Multimedialnych

    * technologie archiwizacji, rekonstrukcji i dostępu do nagrań archiwalnych * technologie inteligentnego monitoringu wizyjnego i akustycznego * multimedialne technologie telemedyczne * multimodalne interfejsy komputerowe

Best results in : Business Offer Pokaż wszystkie wyniki (25)

Search results for: UNSUPERVISED MACHINE LEARNING

Other results Pokaż wszystkie wyniki (1855)

Search results for: UNSUPERVISED MACHINE LEARNING

  • Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance

    Publication
    • K. Saboo
    • Y. Varatharajah
    • B. M. Berry
    • V. Kremen
    • M. R. Sperling
    • K. A. Davis
    • B. C. Jobst
    • R. E. Gross
    • B. C. Lega
    • S. A. Sheth... and 3 others

    - Scientific Reports - Year 2019

    Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable...

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  • MACHINE LEARNING

    Journals

    ISSN: 0885-6125 , eISSN: 1573-0565

  • Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis

    We proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...

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  • Speech Analytics Based on Machine Learning

    Publication

    In this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...

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  • Explainable machine learning for diffraction patterns

    Publication
    • S. Nawaz
    • V. Rahmani
    • D. Pennicard
    • S. P. R. Setty
    • B. Klaudel
    • H. Graafsma

    - Journal of Applied Crystallography - Year 2023

    Serial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...

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