Essays about: "sekventiell"
Showing result 1 - 5 of 92 essays containing the word sekventiell.
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1. AI/ML Development for RAN Applications : Deep Learning in Log Event Prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Since many log tracing application and diagnostic commands are now available on nodes at base station, event log can easily be collected, parsed and structured for network performance analysis. In order to improve In Service Performance of customer network, a sequential machine learning model can be trained, test, and deployed on each node to learn from the past events to predict future crashes or a failure. READ MORE
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2. A Gradient Boosting Tree Approach for Behavioural Credit Scoring
University essay from KTH/Matematisk statistikAbstract : This report evaluates the possibility of using sequential learning in a material development setting to help predict material properties and speed up the development of new materials. To do this a Random forest model was built incorporating carefully calibrated prediction uncertainty estimates. READ MORE
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3. Multi-Scale Task Dynamics in Transfer and Multi-Task Learning : Towards Efficient Perception for Autonomous Driving
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Autonomous driving technology has the potential to revolutionize the way we think about transportation and its impact on society. Perceiving the environment is a key aspect of autonomous driving, which involves multiple computer vision tasks. READ MORE
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4. Syntax-Based Dependency Discovery : Extracting Dependencies Between Integration Test Cases for Passive Testing
University essay from KTH/Hälsoinformatik och logistikAbstract : Modern-day vehicles consist of numerous electronic computing devices with accompanying software. Since vehicles are generally classified as safety-critical systems, rigorous testing strategies have to be deployed to ensure correct operation of the embedded software. READ MORE
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5. Explainable Machine Learning in Cardiovascular Diagnostics
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The major challenges in implementing machine learning models in medical applications stemfrom ethical and accountability concerns, which arise from the lack of insight and understandingof the models' inner workings and reasoning. This opaqueness has resulted in the emergenceof a new subfield of machine learning called Explainability, which aims to develop and deploymethods to gain insight into how input data is weighted and propagated through a machinelearning algorithm. READ MORE