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2. Cross-lingual embeddings for hate speech detection in commentsRok Marinšek, 2019, magistrsko delo/naloga Ključne besede: word embedding, cross-lingual embedding, deep learning, hate speech detection, natural language processing, RCSLS method, BERT language model Celotno besedilo (datoteka, 648,50 KB) |
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4. Fast and accurate Monte Carlo simulations of subdiffusive spatially resolved reflectance for a realistic optical fiber probe tip model aided by a deep neural networkYevhen Zelinskyi, Peter Naglič, Franjo Pernuš, Boštjan Likar, Miran Bürmen, 2020, izvirni znanstveni članek Ključne besede: light propagation model, Monte Carlo simulations, absorption, subdiffusive spatially resolved reflectance, optical fiber probe, deep neural networks, deep learning Celotno besedilo (datoteka, 3,68 MB) Gradivo ima več datotek! Več... |
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6. Human-centered deep compositional model for handling occlusionsGregor Koporec, Janez Perš, 2023, izvirni znanstveni članek Ključne besede: computer vision, deep learning, convolutional neural networks, hierarchical compositional model, occlusion, discriminability, generalizability, interpretability, domain knowledge, instance segmentation, occlusion handling Celotno besedilo (datoteka, 2,69 MB) Gradivo ima več datotek! Več... |
7. IPADMatej Vitek, Matic Bizjak, Peter Peer, Vitomir Štruc, 2023, izvirni znanstveni članek Ključne besede: biometrics, sclera segmentation, ocular biometrics, ocular segmentation, model pruning, lightweight deep learning Celotno besedilo (datoteka, 4,52 MB) Gradivo ima več datotek! Več... |
8. A global modeling framework for load forecasting in distribution networksMiha Grabner, Yi Wang, Qingsong Wen, Boštjan Blažič, Vitomir Štruc, 2023, izvirni znanstveni članek Ključne besede: load forecasting, distribution networks, predictive models, smart meter, global model, deep learning Celotno besedilo (datoteka, 2,89 MB) Gradivo ima več datotek! Več... |
9. Extensive T1-weighted MRI preprocessing improves generalizability of deep brain age prediction modelsLara Dular, Franjo Pernuš, Žiga Špiclin, 2024, izvirni znanstveni članek Ključne besede: magnetic resonance imaging, brain age prediction, image preprocessing, deep model regression, comparative study, quantitative evaluation, brain age, MRI preprocessing, deep regression models, linear mixed effect models, dataset bias, transfer learning, reproducible research, UK Biobank Celotno besedilo (datoteka, 4,29 MB) Gradivo ima več datotek! Več... |