|
72. Advanced PV performance modelling based on different levels of irradiance data accuracyJulián Andrés Ascencio Vásquez, Jakob Bevc, Kristjan Reba, Kristijan Brecl, Marko Jankovec, Marko Topič, 2020, izvirni znanstveni članek Ključne besede: PV performance modelling, data filtering, PV systems, machine learning, lightGBM Celotno besedilo (datoteka, 5,05 MB) Gradivo ima več datotek! Več... |
73. Analysis of command and control connections using machine learning algorithmsJAKOB PREMRN, 2020, magistrsko delo/naloga Ključne besede: machine learning, imbalanced dataset, command and control, C2, C&C, Zeek, Random forest, Decision tree Celotno besedilo (datoteka, 4,92 MB) |
74. Forecasting electricity pricesMauro Castelli, Aleš Groznik, Aleš Popovič, 2020, izvirni znanstveni članek Ključne besede: energetics, price, informatics, energy sector, electricity prices, forecasting, machine learning, geometric semantic, based programming Celotno besedilo (datoteka, 2,00 MB) Gradivo ima več datotek! Več... |
|
|
77. Search for type-III seesaw heavy leptons with the ATLAS detector at the LHCTadej Novak, 2020, doktorska disertacija Ključne besede: seesaw mechanism, type-III seesaw, fermion triplet, machine learning, boosted decision trees, neural networks, ATLAS, CERN, LHC Run 2, dilepton, two jets, missing transverse energy Celotno besedilo (datoteka, 6,47 MB) |
78. Comparative study of first order optimizers for image classification using convolutional neural networks on histopathology imagesIbrahem Kandel, Mauro Castelli, Aleš Popovič, 2020, izvirni znanstveni članek Ključne besede: image classification, convolutional neural networks, deep learning, medical images, transfer learning, optimizers, neuroscience Celotno besedilo (datoteka, 573,18 KB) Gradivo ima več datotek! Več... |
79. Recovery of superquadric parameters from depth images using deep learningTim Oblak, 2020, magistrsko delo Ključne besede: superquadrics, parametric models, reconstruction, 3D, deep learning, convolutional neural networks, CNN, parameter recovery Celotno besedilo (datoteka, 8,69 MB) |
|