Sökning: "Övervakad Maskininlärning"

Visar resultat 1 - 5 av 74 uppsatser innehållade orden Övervakad Maskininlärning.

1. 1. Physical Exercise and Fatigue Detection using Machine Learning

   Uppsats för yrkesexamina på grundnivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Filip Säterberg; Rasmus Nilsson; [2024]
   Nyckelord :Machine Learning; Fatigue Prediction; Data Collection; Supervised learning; Surface Electromyography; Accelerometers; Maskininlärning; Trötthetsförutsägelse; Datainsamling; Övervakad; Ytlig-elektromyografi Accelerometrar;

   Sammanfattning : Monitoring of physical exercise is an important task to evaluate and adapt exercise to provide better exercise results. The Inno-X™ device, developed by Innowearable, is a device that can be used for such monitoring. It collects data using an accelerometer and sEMG sensor. LÄS MER

3. 2. Analyzing How Blended Emotions are Expressed using Machine Learning Methods

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Disen Ling; [2023]
   Nyckelord :Blended emotion; Supervised learning; Model generalization capability; Ablation study; Blandade känslor; Övervakad inlärning; Modellens generaliseringsförmåga; Ablationsstudie;

   Sammanfattning : Blended emotion is a classification of emotional experiences that involve the combination of multiple emotions. Research on the expression of blended emotions allows researchers to understand how different emotions interact and coexist in an individual’s emotional experience. LÄS MER

4. 3. Developing Automated Cell Segmentation Models Intended for MERFISH Analysis of the Cardiac Tissue by Deploying Supervised Machine Learning Algorithms

   Master-uppsats, KTH/Kemi

   Författare :Julia Rune; [2023]
   Nyckelord :Cell Segmentation; Cellpose; Supervised Machine Learning; MERFISH; Heart Failure; Cellsegmentering; Cellpose; Övervakad Maskininlärning; MERFISH; Hjärtsvikt;

   Sammanfattning : Följande studie behandlar utvecklandet av automatiserade cellsegmenteringsmodeller med avsikt att identifiera gränser mellan celler i hjärtvävnad. Syftet är att möjliggöra analys av data genererad från multiplexed error-robust in situ hybridization (MERFISH). LÄS MER

5. 4. Rotor temperature estimation in Induction Motors with Supervised Machine Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Christopher Gauffin; [2023]
   Nyckelord :Induction motors; Supervised Machine learning; Power converters; Parameter estimation; Embedded systems; Induktionsmotorer; Övervakad maskininlärning; Strömkonverterare; Parameterestimering; Inbyggda system;

   Sammanfattning : The electrification of the automotive industry and artificial intelligence are both growing rapidly and can be greatly beneficial for a more sustainable future when combined. Induction machines exhibit many complex relationships between physical and electromagnetic properties that must be calculated in order to produce the correct quantities of torque and speed commanded by the driver. LÄS MER

7. 5. Evaluating machine learning models for time series forecasting in smart buildings

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Sarugan Balachandran; Diego Perez Legrand; [2023]
   Nyckelord :Machine learning; supervised learning; time series forecasting; neural networks; LSTM; En- semble LSTM; AT-LSTM; ARIMA; XGBoost; Maskininlärning; övervakad inlärning; tidsserie-prognostisering; neurala nätverk; LSTM; En- semble LSTM; AT-LSTM; ARIMA; XGBoost;

   Sammanfattning : Temperature regulation in buildings can be tricky and expensive. A common problem when heating buildings is that an unnecessary amount of energy is supplied. This waste of energy is often caused by a faulty regulation system. LÄS MER