Search for dissertations about: "Activity recognition"
Showing result 1 - 5 of 241 swedish dissertations containing the words Activity recognition.
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1. Complex activity recognition and context validation within social interaction tools
Abstract : Human activity recognition using sensing technology is crucial in achieving pervasive and ubiquitous computing paradigms. It can be applied in many domains such as health-care, aged-care, personal-informatics, industry, sports and military. READ MORE
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2. Planning in Inhabited Environments : Human-Aware Task Planning and Activity Recognition
Abstract : Promised some decades ago by researchers in artificial intelligence and robotics as an imminent breakthrough in our everyday lives, a robotic assistant that could work with us in our home and our workplace is a dream still far from being fulfilled. The work presented in this thesis aims at bringing this future vision a little closer to realization. READ MORE
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3. Peptidoglycan Recognition Proteins : Major Regulators of Drosophila Immunity
Abstract : All eukaryotic organisms have an innate immune system characterized by germ-line encoded receptors and effector molecules, which mediate detection and clearance of microbes such as bacteria, fungi, and parasites. VertebrateDrosophila as a genetically tractable organism with a This thesis concerns the peptidoglycan recognition protein (PGRP) gene family in the fruit fly. READ MORE
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4. Learning Representations for Machine Activity Recognition
Abstract : Machine activity recognition (MAR) is an essential and effective approach for equipment productivity monitoring. Developing MAR methods for forklift trucks, a vital piece of the industry, can benefit productivity efficiency, maintenance service, product design, and potential savings. READ MORE
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5. Unobtrusive Activity Recognition in Resource-Constrained Environments
Abstract : This thesis discusses activity recognition from a perspective of unobtrusiveness, where devices are worn or placed in the environment without being stigmatising or in the way. The research focuses on performing unobtrusive activity recognition when computational and sensing resources are scarce. READ MORE