Search for dissertations about: "Autonomous learning"
Showing result 1 - 5 of 150 swedish dissertations containing the words Autonomous learning.
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1. Sharing to learn and learning to share : Fitting together metalearning and multi-task learning
Abstract : This thesis focuses on integrating learning paradigms that ‘share to learn,’ i.e., Multitask Learning (MTL), and ‘learn (how) to share,’ i.e. READ MORE
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2. Learning from Interactions : Forward and Inverse Decision-Making for Autonomous Dynamical Systems
Abstract : Decision-making is the mechanism of using available information to generate solutions to given problems by forming preferences, beliefs, and selecting courses of action amongst several alternatives. In this thesis, we study the mechanisms that generate behavior (the forward problem) and how their characteristics can explain observed behavior (the inverse problem). READ MORE
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3. Terrain machine learning
Abstract : The use of heavy vehicles in rough terrain is vital in the industry but has negative implications for the climate and ecosystem. In addition, the demand for improved efficiency underscores the need to enhance these vehicles' navigation capabilities. READ MORE
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4. Learning visual perception for autonomous systems
Abstract : In the last decade, developments in hardware, sensors and software have made it possible to create increasingly autonomous systems. These systems can be as simple as limited driver assistance software lane-following in cars, or limited collision warning systems for otherwise manually piloted drones. READ MORE
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5. Deep Learning Applications for Autonomous Driving
Abstract : This thesis investigates the usefulness of deep learning methods for solving two important tasks in the field of driving automation: (i) Road detection, and (ii) driving path generation. Road detection was approached using two strategies: The first one considered a bird's-eye view of the driving scene obtained from LIDAR data, whereas the second carried out camera-LIDAR fusion in the camera perspective. READ MORE