Sökning: "Övervakad klassificering"

Visar resultat 1 - 5 av 27 uppsatser innehållade orden Övervakad klassificering.

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. Classification of Radar Emitters using Semi-Supervised Contrastive Learning

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

   Författare :Tim Jonsson; [2023]
   Nyckelord :;

   Sammanfattning : Radar is a commonly used radio equipment in military and civilian settings for discovering and locating foreign objects. In a military context, pilots being discovered by radar could have fatal consequences. LÄS MER

5. 4. ML enhanced interpretation of failed test result

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

   Författare :Hiranmayi Pechetti; [2023]
   Nyckelord :Data Parsing; Machine Learning; Log file Analysis; Text Classification; Supervised Classification; Dataanalys; maskininlärning; loggfilsanalys; textklassificering; Övervakad klassificering;

   Sammanfattning : This master thesis addresses the problem of classifying test failures in Ericsson AB’s BAIT test framework, specifically distinguishing between environment faults and product faults. The project aims to automate the initial defect classification process, reducing manual work and facilitating faster debugging. LÄS MER

7. 5. Methods for data and user efficient annotation for multi-label topic classification

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

   Författare :Agnieszka Miszkurka; [2022]
   Nyckelord :Natural Language Processing; Multi-label text classification; Active Learning; Zero-shot learning; Data Augmentation; Data-centric AI; Naturlig språkbehandling; Textklassificering med multipla klasser; Active Learning; Zero-shot learning; Data Augmentation; Datacentrerad AI;

   Sammanfattning : Machine Learning models trained using supervised learning can achieve great results when a sufficient amount of labeled data is used. However, the annotation process is a costly and time-consuming task. There are many methods devised to make the annotation pipeline more user and data efficient. LÄS MER