Sökning: "lth"
Visar resultat 1 - 5 av 670 uppsatser innehållade ordet lth.
1. Using NeRF- and Mesh-Based Methods to Improve Visualisation of Point Clouds
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : In recent years, the field of generating synthetic images from novel view points has seen some major improvements. Most importantly with the publication of Neural Radiance Fields allowing for extremely detailed and accurate 3D novel views. LÄS MER
2. Magic Tree - Development of a technology mediating multi-sensory musical instrument
Master-uppsats, Lunds universitet/InnovationSammanfattning : This thesis is part of the MISK-project, Musik, Interaktiv design, Sinnesstimulering och Kvalitet (Music, Interactive design, Sensory stimulation and Quality). The MISK-project is a collaborative project between Certec at LTH, Furuboda Folkhögskola and Eldorado Resurscenter, developing musical instruments for children and young adults with mental and physical disabilities. LÄS MER
3. Klimatanpassning av svensk järnväg ur ett riskperspektiv - Var står vi och vart är vi på väg
Master-uppsats, Lunds universitet/Riskhantering (CI); Lunds universitet/Avdelningen för Riskhantering och SamhällssäkerhetSammanfattning : The world faces significant climate changes with potential societal disruptions and risks to critical infrastructure like railways. This study explores the topic of climate change, extreme weather, and changing travel patterns for Swedish railways. LÄS MER
4. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER
5. Virtual H&E Staining Using PLS Microscopy and Neural Networks
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER