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  • machine learning
  • KIT Scientific Publishing  (5)
  • Karolinum Press  (1)
  • English  (6)
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  • 1
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    Proceedings of the 2020 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory (2021)
    KIT Scientific Publishing | KIT Scientific Publishing
    Details
    Publication Date: 2024-04-14
    Description: In 2020, the annual joint workshop of the Fraunhofer IOSB and the Vision and Fusion Laboratory of the KIT was hosted at the IOSB in Karlsruhe. For a week from the 27th to the 31st July the doctoral students of both institutions presented extensive reports on the status of their research and discussed topics ranging from computer vision and optical metrology to network security, usage control and machine learning. The results and ideas presented at the workshop are collected in this book.
    Keywords: KI ; maschinelles Lernen ; computer vision ; usage control ; Metrologie ; machine learning ; metrology ; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
    Language: English
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  • 2
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    A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation (2022)
    KIT Scientific Publishing | KIT Scientific Publishing
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    Publication Date: 2024-04-11
    Description: The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.
    Keywords: Vorhofflimmern ; Fibrose ; maschinelles Lernen ; Bidomain ; Modellierung des Herzens ; atrial fibrillation ; fibrosis ; machine learning ; bidomain ; cardiac modeling ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
    Language: English
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  • 3
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    Versification and Authorship Attribution (2022)
    Karolinum Press
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    Publication Date: 2024-04-04
    Description: The technique known as contemporary stylometry uses different methods, including machine learning, to discover a poem’s author based on features like the frequencies of words and character n-grams. However, there is one potential textual fingerprint stylometry tends to ignore: versification, or the very making of language into verse. Using poetic texts in three different languages (Czech, German, and Spanish), Petr Plecháč asks whether versification features like rhythm patterns and types of rhyme can help determine authorship. He then tests its findings on two unsolved literary mysteries. In the first, Plecháč distinguishes the parts of the Elizabethan verse play The Two Noble Kinsmen written by William Shakespeare from those written by his coauthor, John Fletcher. In the second, he seeks to solve a case of suspected forgery: how authentic was a group of poems first published as the work of the nineteenth-century Russian author Gavriil Stepanovich Batenkov? This book of poetic investigation should appeal to literary sleuths the world over.
    Keywords: contemporary stylometry ; stylometry ; machine learning ; versification ; authorship ; literary criticism ; statistics ; thema EDItEUR::P Mathematics and Science ; thema EDItEUR::D Biography, Literature and Literary studies
    Language: English
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  • 4
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    Proceedings of the 2019 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory (2022)
    KIT Scientific Publishing | KIT Scientific Publishing
    Details
    Publication Date: 2024-03-30
    Description: In 2019 again, the annual joint workshop of the Fraunhofer IOSB and the Vision and Fusion Laboratory of the Karlsruhe Institute of Technology took place. The doctoral students of both institutions presented extensive reports on the status of their research and discussed topics ranging from computer vision and optical metrology to network security, usage control and machine learning. The results and ideas presented at the workshop are collected in this book in the form of technical reports.
    Keywords: usage control ; network security ; metrology ; machine vision ; machine learning ; Usage Control ; Netzwerksicherheit ; Messtechnik ; Machine Vision ; Maschinelles Lernen
    Language: English
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  • 5
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    Efficient Reinforcement Learning using Gaussian Processes (2021)
    KIT Scientific Publishing
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    Publication Date: 2023-12-20
    Description: This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fully Bayesian approach for efficient RL in continuous-valued state and action spaces when no expert knowledge is available. PILCO takes model uncertainties consistently into account during long-term planning to reduce model bias. Second, we propose principled algorithms for robust filtering and smoothing in GP dynamic systems.
    Keywords: QA75.5-76.95 ; autonomous learning ; Gaussian processes ; control ; machine learning ; Bayesian inference ; bic Book Industry Communication::U Computing & information technology::UY Computer science
    Language: English
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  • 6
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    Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms (2021)
    KIT Scientific Publishing
    Details
    Publication Date: 2023-07-05
    Description: This work is a contribution to understanding multi-object traffic scenes from video sequences. All data is provided by a camera system which is mounted on top of the autonomous driving platform AnnieWAY. The proposed probabilistic generative model reasons jointly about the 3D scene layout as well as the 3D location and orientation of objects in the scene. In particular, the scene topology, geometry as well as traffic activities are inferred from short video sequences.
    Keywords: QA75.5-76.95 ; computer vision ; machine learning ; scene understanding
    Language: English
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