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Showing result 1 - 5 of 729 essays matching the above criteria.
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1. An In-Depth study on the Utilization of Large Language Models for Test Case Generation
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : This study investigates the utilization of Large Language Models for Test Case Generation. The study uses the Large Language model and Embedding model provided by Llama, specifically Llama2 of size 7B, to generate test cases given a defined input. READ MORE
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2. Are Distributional Variables Useful for Forecasting With the Phillips Curve?
University essay from Handelshögskolan i Stockholm/Institutionen för nationalekonomiAbstract : Does information on the distribution of wealth and income help us forecast aggregate macroeconomic variables? In this thesis, we study how adding such distributional variables to a standard forecasting model affects the forecast accuracy, in the context of inflation forecasting. Using the simulated inflation forecasting approach of Atkeson and Ohanian (2001), we perform a horse race between a textbook NAIRU Phillips curve to an extension augmented with variables from the wealth and income distributions. READ MORE
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3. Machine Learning for Spatial Positioning for XR Environments
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : This bachelor's thesis explores the integration of machine learning (ML) with sensor fusion techniques to enhance spatial data accuracy in Extended Reality (XR) environments. With XR's revolutionary impact across various sectors, accurate localization in virtual environments becomes imperative. READ MORE
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4. Automatic Semantic Segmentation of Indoor Datasets
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. READ MORE
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5. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. READ MORE