21. Development of a real-time motor-imagery-based EEG brain-machine interfaceGal Gorjup, Rok Vrabič, Stoyan Petrov Stoyanov, Morten Østergaard Andersen, Poramate Manoonpong, 2018, objavljeni znanstveni prispevek na konferenci Ključne besede: electroencephalography, brain-machine interface, brain-computer interface, motor imagery, digital filtering, feature extraction, classification Celotno besedilo (datoteka, 10,69 MB) Gradivo ima več datotek! Več... |
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23. Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)Milan Sencanski, Sanja Glisic, Marko Šnajder, Nevena Veljković, Nataša Poklar Ulrih, Janez Mavri, Milka Vrecl, 2019, izvirni znanstveni članek Ključne besede: molecular biology, computer simulation, receptors, adrenergic, β2 – metabolism – chemistry, peptidomimetics – chemical synthesis, single-domain antibodies – chemistry Celotno besedilo (datoteka, 2,37 MB) Gradivo ima več datotek! Več... |
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27. An empirical investigation of forecasting stock market volatility with support vector machinesCheng Yao, 2020, magistrsko delo Ključne besede: capital market, shares, stock exchange, trading, economic forecasting, evaluation, models, vector analysis, computer application Celotno besedilo (povezava drugam) |
28. Musculoskeletal images classification for detection of fractures using transfer learningIbrahem Kandel, Mauro Castelli, Aleš Popovič, 2020, izvirni znanstveni članek Ključne besede: transfer learning, computer vision, convolutional neural networks, image classification, musculoskeletal images, deep learning, medical images, neuroscience Celotno besedilo (datoteka, 550,23 KB) Gradivo ima več datotek! Več... |
29. Quantitative contact-less estimation of energy expenditure from video and 3D imageryGregor Koporec, Goran Vučković, Radoje Milić, Janez Perš, 2018, izvirni znanstveni članek Ključne besede: physical activity, energy expenditure, computer vision, optical flow, scene flow, heart rate, support vector machine, RBF kernel, KCF tracker, Microsoft Kinect, time-of-flight sensor, squash Celotno besedilo (datoteka, 7,87 MB) Gradivo ima več datotek! Več... |
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