Sökning: "KTH bildanalys"
Visar resultat 1 - 5 av 48 uppsatser innehållade orden KTH bildanalys.
1. Robustness Analysis of Perfusion Parameter Calculations
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cancer is one of the most common causes of death worldwide. When given optimal treatment, however, the risk of severe illness may greatly be reduced. Determining optimal treatment in turn requires evaluation of disease progression and response to potential, previous treatment. LÄS MER
2. Evaluation of a computational method for natural fiber-reinforced plastics
Master-uppsats, KTH/HållfasthetsläraSammanfattning : The importance of using natural fiber composites (NFCs) has been addressed as a substitution for synthetic fibers, such as glass and carbon fibers. This substitution contributes significantly to reducing greenhouse gas emissions, aligning with the environmental responsibilities of engineering industries. LÄS MER
3. Machine learning-assisted image analysis and metabarcoding for monitoring of plankton in the seas surrounding Sweden
Master-uppsats, KTH/Industriell bioteknologiSammanfattning : I miljöövervakningen av haven runt Sverige har manuell mikroskopi av plankton länge varit den huvudsakliga tekniken för att övervaka växtplanktonbestånden och algblomningar. Nya tekniker utvärderas, men det är inte känt hur resultaten från de nyare teknikerna relaterar till varandra. LÄS MER
4. Apparent density for water atomized low-carbon steel powder
Master-uppsats, KTH/MaterialvetenskapSammanfattning : Carbon content does not affect the apparent density for water atomized iron powder monotonically. At low carbon content, around 0.1 wt %, apparent density is higher than a similar powder with 0.3 wt % carbon. LÄS MER
5. Neuromorphic Medical Image Analysis at the Edge : On-Edge training with the Akida Brainchip
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Computed Tomography (CT) scans play a crucial role in medical imaging, allowing neuroscientists to identify intracranial pathologies such as haemorrhages and malignant tumours in the brain. This thesis explores the potential of deep learning models as an aid in intracranial pathology detection through medical imaging. LÄS MER