Sökning: "Hybrida Modeller"
Visar resultat 1 - 5 av 11 uppsatser innehållade orden Hybrida Modeller.
1. "Frihet under ansvar"- funkar det lika bra hemma som på ett kontor? : Hybridarbetets påverkan på ledarskapet
Kandidat-uppsats, Karlstads universitet/Handelshögskolan (from 2013)Sammanfattning : Denna kandidatuppsats syftar till att undersöka hur ledares ledarskap förändrats då medarbetarna arbetar på ett hybridarbetssätt. Uppsatsen undersöker, genom en kvalitativ ansats, hur ledare under och efter Covid-19 har agerat i det nya hybrida arbetssättet och deras inställning till det. LÄS MER
2. 3D Gaze Estimation on Near Infrared Images Using Vision Transformers
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Gaze estimation is the process of determining where a person is looking, which has recently become a popular research area due to its broad range of applications. For example, tools that estimate gaze are used for research, medical diagnosis, virtual and augmented reality, driver assistance system, and many more. LÄS MER
3. Produktutveckling för framtidens arbetsplatser
Master-uppsats, Lunds universitet/InnovationSammanfattning : Companies have implemented major changes due to the recommendations of remote work introduced by the Swedish Public Health Agency as a result of the Covid-19 pandemic. Remote work has rapidly increased, and the forecast is that this flexible working method will remain. LÄS MER
4. Real-time refraction through multiple layers using image-space method with inline ray tracing
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Although modern hardware allows us to use ray tracing in real-time, ray traced refractions are still demanding due to its need to generate multiple rays recursively in order to fully refract through a multi-layered object. With the recent release of inline ray tracing, it is possible to traverse and register ray hits inside a fragment shader. LÄS MER
5. Hybrid Ensemble Methods: Interpretible Machine Learning for High Risk Aeras
Master-uppsats, KTH/Matematisk statistikSammanfattning : Despite the access to enormous amounts of data, there is a holdback in the usage of machine learning in the Cyber Security field due to the lack of interpretability of ”Blackbox” models and due to heterogenerous data. This project presents a method that provide insights in the decision making process in Cyber Security classification. LÄS MER