Sökning: "perceptron"
Visar resultat 6 - 10 av 171 uppsatser innehållade ordet perceptron.
6. Machine Learning of Laser Ultrasonic Data to Predict Material Properties
Master-uppsats, Linköpings universitet/Statistik och maskininlärningSammanfattning : The hardness of steel is an important quality parameter for several industrial applications. Conventional mechanical testing is used in quality testing for material hardness and the method is time-consuming, can cause material mix-ups, and results in material waste. LÄS MER
7. Machine Learning based Predictive Data Analytics for Embedded Test Systems
Kandidat-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Organizations gather enormous amounts of data and analyze these data to extract insights that can be useful for them and help them to make better decisions. Predictive data analytics is a crucial subfield within data analytics that make accurate predictions. Predictive data analytics extracts insights from data by using machine learning algorithms. LÄS MER
8. Automatic Analysis of Peer Feedback using Machine Learning and Explainable Artificial Intelligence
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Peer assessment is a process where learners evaluate and provide feedback on one another’s performance, which is critical to the student learning process. Earlier research has shown that it can improve student learning outcomes in various settings, including the setting of engineering education, in which collaborative teaching and learning activities are common. LÄS MER
9. Link Prediction Using Learnable Topology Augmentation
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : Link prediction is a crucial task in many downstream applications of graph machine learning. Graph Neural Networks (GNNs) are a prominent approach for transductive link prediction, where the aim is to predict missing links or connections only within the existing nodes of a given graph. LÄS MER
10. Cell Tower Localization using crowdsourced measurments
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis explores the application of a neural network approach to cell tower localization using crowdsourced measurements. The deployment of cell tower infrastructure has been increasing exponentially in recent times as it is a crucial element of mobile communications. LÄS MER