Suche
Anzeige der Dokumente 251-255 von 255
Dissertation
Patterns of Practice - Interdisciplinary Negotiation of Cultural Complexity through Practice-Based Methods in Informatics
(2022)
Following the principle of knowing through making, this thesis discusses development and application of a practice-based methodology for construction of digital artefacts within
cultural contexts. It addresses the epistemological diversity and complexity inhering within interdisciplinary projects, suggesting methodological devices able to navigate the variegated disciplinary landscape present within respective development projects. The conceptual pair complexity/complication acts as theoretical point of reference ...
Zeitschrift
Jahresbericht 2023
(Universität Kassel, Fachbereich Wirtschaftswissenschaften, 2024)
Dissertation
Context Awareness for Smartphone-Based Cooperative VRU Collision Avoidance
(2024)
Nach Angaben der Weltgesundheitsorganisation sterben weltweit noch immer jährlich rund 1,35 Millionen Menschen bei Verkehrsunfällen. Ungefähr 54% dieser Todesfälle ereignen sich unter ungeschützten Verkehrsteilnehmern wie Fußgängern, Radfahrern und Motorradfahrern. Fußgänger und Radfahrer machen dabei zusammen rund 26% aller Verkehrstoten aus. Im Gegensatz zu fahrzeugbasierten Kollisionsvermeidungssystemen setzen kooperative Systeme die Verwendung von mobilen Geräten wie Smartphones zur kontinuierlichen Erfassung von ...
Aufsatz
Continuous Feature Networks: A Novel Method to Process Irregularly and Inconsistently Sampled Data With Position-Dependent Features
(2023-12-30)
Continuous Kernels have been a recent development in convolutional neural networks. Such kernels are used to process data sampled at different resolutions as well as irregularly and inconsistently sampled data. Convolutional neural networks have the property of translational invariance (e.g., features are detected regardless of their position in the measurement domain), which is unsuitable if the position of detected features is relevant for the prediction task. However, the capabilities of continuous kernels to ...
Konferenzveröffentlichung
Utilizing Continuous Kernels for Processing Irregularly and Inconsistently Sampled Data With Position-Dependent Features
(2023-03-13)
Continuous Kernels have been a recent development in convolutional neural networks. Such kernels are used to process data sampled at different resolutions as well as irregularly and inconsistently sampled data. Convolutional neural networks have the property of translational invariance (e.g., features are detected regardless of their position in the measurement domain), which is unsuitable for certain types of data, where the position of detected features is relevant. However, the capabilities of continuous kernels ...