Sökning: "statistical classifiers"
Visar resultat 1 - 5 av 40 uppsatser innehållade orden statistical classifiers.
1. Multiclass Brain Tumour Tissue Classification on Histopathology Images Using Vision Transformers
Master-uppsats, Linköpings universitet/Statistik och maskininlärningSammanfattning : Histopathology refers to inspecting and analysing tissue samples under a microscope to identify and examine signs of diseases. The manual investigation procedure of histology slides by pathologists is time-consuming and susceptible to misconceptions. LÄS MER
2. Development of a Digital Coaching Application with Automated Mistake Identification using a Multi-Sensor Configuration
Master-uppsats, KTH/Medicinteknik och hälsosystemSammanfattning : Home-based exercise is a popular physical activity of maintaining fitness, health andwellness in general. However, without proper supervision and basic knowledge of theexercises in the workout plan, there is an increased risk of injury. LÄS MER
3. Comparing Ensemble Methods with Individual Classifiers in Machine Learning for Diabetes Detection
Kandidat-uppsats, KTH/DatavetenskapSammanfattning : Diabetes is a common disease that is characterized by several health markers. These markers can be used in machine learning to help predict the presence of diabetes in an individual. LÄS MER
4. Identification and network analysis of candidate microRNA biomarkers in neuroblastoma : A meta-analysis
Master-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : Neuroblastoma constitutes roughly 8% of all childhood cancers where 95% of all neuroblastoma cases occur before the age of 10. The survival rate of infants and young children is very poor, which alone contributes to research novel biomarkers for classification methods, improved diagnosis and better anti-tumor therapies. LÄS MER
5. Presence detection by means of RF waveform classification
Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : This master thesis investigates the possibility to automatically label and classify radio waves for presence detection, where the objective is to obtain information about the number of people in a room based on channel estimates. Labeling data for machine learning is time consuming and tedious process. To address this two approaches are evaluated. LÄS MER