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2. Learning basic object affordances in a robotic systemBarry Ridge, 2014, doktorska disertacija Ključne besede: affordances, affordance learning, self-supervised learning, multi-view learning, cross-modal learning, multi-modal learning, feature relevance determination, online learning, cognitive robotics, developmental robotics, doctoral dissertations, theses Celotno besedilo (datoteka, 17,34 MB) |
3. Reinforcement-learning-based route generation for heavy-traffic autonomous mobile robot systemsDominik Kozjek, Andreja Malus, Rok Vrabič, 2021, izvirni znanstveni članek Ključne besede: intralogistics, autonomous mobile robots, multi-robot cooperation, reinforcement learning, route planning Celotno besedilo (datoteka, 23,99 MB) Gradivo ima več datotek! Več... |
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6. Application of temporal convolutional neural network for the classification of crops on Sentinel-2 time seriesMatej Račič, Krištof Oštir, Devis Peressutti, Anže Zupanc, Luka Čehovin Zajc, 2020, objavljeni znanstveni prispevek na konferenci Ključne besede: deep learning, multi-temporal classification, sequence data, crop classification, Sentinel-2 Celotno besedilo (povezava drugam) |
7. Learning and diffusion of knowledge in clean energy communitiesPrimož Medved, Urša Golob, Tanja Kamin, 2023, izvirni znanstveni članek Ključne besede: clean energy community, learning settings, diffusion of knowledge, energy transition, transactional learning theory, multi-level perspective, niche innovation, renewable energy Celotno besedilo (datoteka, 1,63 MB) Gradivo ima več datotek! Več... |
8. Multi-task learning in programmatic advertisingDOMEN VREŠ, 2023, magistrsko delo Ključne besede: artificial intelligence, machine learning, multi-task learning, real-time bidding, viewability prediction, click-through rate prediction, conversion rate prediction, deep & cross network, cross-stitch layer, soft attention, uncertainty based loss weighing Celotno besedilo (datoteka, 1,39 MB) |
9. CLUSPLUSMatej Petković, Jurica Levatić, Dragi Kocev, Martin Breskvar, Sašo Džeroski, 2023, izvirni znanstveni članek Ključne besede: machine learning, multi-target regression, multi-label classification, decision trees, feature importance, semi-supervised learning, random forests Celotno besedilo (datoteka, 563,19 KB) Gradivo ima več datotek! Več... |