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Wyniki wyszukiwania dla: neural networks

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Wyniki wyszukiwania dla: neural networks

  • From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies

    In this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...

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  • Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction

    Publikacja

    - Scientific Reports - Rok 2023

    This work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...

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  • Synteza układu sterowania statkiem morskim dynamicznie pozycjonowanym w warunkach niepewności

    Publikacja

    - Rok 2019

    Niniejsza monografia obejmuje zagadnienia związane z syntezą układu dynamicznego pozycjonowania statku w środowisku morskim z zastosowaniem wybranych nieliniowych metod sterowania. W ramach pracy autorka rozważała struktury sterowania z zastosowaniem wektorowej adaptacyjnej metody backstep oraz metod jej pokrewnych, takich jak regulatory MSS (ang. multiple surface sliding), DSC (ang. dynamic surface control), NB (ang. neural backstepping)....

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  • Emotion Recognition Based on Facial Expressions of Gamers

    This article presents an approach to emotion recognition based on facial expressions of gamers. With application of certain methods crucial features of an analyzed face like eyebrows' shape, eyes and mouth width, height were extracted. Afterwards a group of artificial intelligence methods was applied to classify a given feature set as one of the following emotions: happiness, sadness, anger and fear. The approach presented in this...

  • Information Extraction from Polish Radiology Reports using Language Models

    Publikacja

    Radiology reports are vital elements of directing patient care. They are usually delivered in free text form, which makes them prone to errors, such as omission in reporting radiological findings and using difficult-to-comprehend mental shortcuts. Although structured reporting is the recommended method, its adoption continues to be limited. Radiologists find structured reports too limiting and burdensome. In this paper, we propose...

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  • Bimodal deep learning model for subjectively enhanced emotion classification in films

    Publikacja

    - INFORMATION SCIENCES - Rok 2024

    This research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....

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  • Dysfunctional prefrontal cortical network activity and interactions following cannabinoid receptor activation.

    Publikacja

    - Journal of Neuroscience - Rok 2011

    Coordinated activity spanning anatomically distributed neuronal networks underpins cognition and mediates limbic-cortical interactions during learning, memory, and decision-making. We used CP55940, a potent agonist of brain cannabinoid receptors known to disrupt coordinated activity in hippocampus, to investigate the roles of network oscillations during hippocampal and medial prefrontal cortical (mPFC) interactions in rats. During...

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  • Human verbal memory encoding is hierarchically distributed in a continuous processing stream

    Publikacja
    • M. T. Kucewicz
    • K. Saboo
    • B. M. Berry
    • V. Kremen
    • L. R. Miller
    • F. Khadjevand
    • C. S. Inman
    • P. A. Wanda
    • M. R. Sperling
    • R. Gorniak... i 8 innych

    - eNeuro - Rok 2019

    Processing of memory is supported by coordinated activity in a network of sensory, association, and motor brain regions. It remains a major challenge to determine where memory is encoded for later retrieval. Here we used direct intracranial brain recordings from epilepsy patients performing free recall tasks to determine the temporal pattern and anatomical distribution of verbal memory encoding across the entire human cortex. High...

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  • High frequency oscillations are associated with cognitive processing in human recognition memory

    Publikacja
    • M. T. Kucewicz
    • J. Cymbalnik
    • J. Matsumoto
    • B. H. Brinkmann
    • M. R. Bower
    • V. Vasoli
    • V. Sulc
    • F. Meyer
    • W. Marsh
    • S. M. Stead
    • G. A. Worrell

    - Brain: A Journal of Neurology - Rok 2014

    High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30-100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations...

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  • A Reduction Method for Bathymetric Datasets that Preserves True Coastal Water Geodata

    Publikacja

    - Remote Sensing - Rok 2019

    Water areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and the objects located on it. Information about the quality and reliability of the depth data is important, especially during coastal modelling. In-shore areas are liable...

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  • Remote Health Monitoring of Wind Turbines Employing Vibroacoustic Transducers and Autoencoders

    Implementation of remote monitoring technology for real wind turbine structures designed to detect potential sources of failure is described. An innovative multi-axis contactless acoustic sensor measuring acoustic intensity as well as previously known accelerometers were used for this purpose. Signal processing methods were proposed, including feature extraction and data analysis. Two strategies were examined: Mel Frequency Cepstral...

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