Sökning: "Träning inlärning"
Visar resultat 11 - 15 av 110 uppsatser innehållade orden Träning inlärning.
11. Lacing a Chord Between Motor Skills and Sonification
Magister-uppsats, Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakultetenSammanfattning : Detta arbete undersöker om sonifiering och användningen av ljud kan förstärka inlärning av sekvenser i muskelminnet. Specifikt undersöks inmatning av sekvenser på en modifierad numpad. Testerna går ut på att se om upprepade inmatningar av samma sekvens ger bättre resultat avseende tid och antal fel, med eller utan ljud som stöd. LÄS MER
12. Semi-Supervised Plant Leaf Detection and Stress Recognition
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : One of the main limitations of training deep learning-based object detection models is the availability of large amounts of data annotations. When annotations are scarce, semi-supervised learning provides frameworks to improve object detection performance by utilising unlabelled data. LÄS MER
13. Energy-Efficient Private Forecasting on Health Data using SNNs
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Health monitoring devices, such as Fitbit, are gaining popularity both as wellness tools and as a source of information for healthcare decisions. Predicting such wellness goals accurately is critical for the users to make informed lifestyle choices. LÄS MER
14. Improving robustness of beyond visual range strategies with adapted training distributions
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : A key obstacle for training an autonomous agent in real air-to-air combat is the lack of available training data, which makes it difficult to apply supervised learning techniques. Self-play is a method that can be used where an agent trains against itself or against versions of itself without imitation data or human instruction. LÄS MER
15. Analysis of Brain Signals from Patients with Parkinson’s Disease using Self-Supervised Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Parkinson’s disease (PD) is one of the most common neurodegenerative brain disorders, commonly diagnosed and monitored via clinical examinations, which can be imprecise and lead to a delayed or inaccurate diagnosis. Therefore, recent research has focused on finding biomarkers by analyzing brain networks’ neural activity to find abnormalities associated with PD pathology. LÄS MER