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You searched for subject:(Logical Sensors). Showing records 1 – 2 of 2 total matches.

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University of Arkansas

1. Hammer, Jon C. Improving the Efficacy of Context-Aware Applications.

Degree: PhD, 2018, University of Arkansas

In this dissertation, we explore methods for enhancing the context-awareness capabilities of modern computers, including mobile devices, tablets, wearables, and traditional computers. Advancements include proposed methods for fusing information from multiple logical sensors, localizing nearby objects using depth sensors, and building models to better understand the content of 2D images. First, we propose a system called Unagi, designed to incorporate multiple logical sensors into a single framework that allows context-aware application developers to easily test new ideas and create novel experiences. Unagi is responsible for collecting data, extracting features, and building personalized models for each individual user. We demonstrate the utility of the system with two applications: adaptive notification filtering and a network content prefetcher. We also thoroughly evaluate the system with respect to predictive accuracy, temporal delay, and power consumption. Next, we discuss a set of techniques that can be used to accurately determine the location of objects near a user in 3D space using a mobile device equipped with both depth and inertial sensors. Using a novel chaining approach, we are able to locate objects farther away than the standard range of the depth sensor without compromising localization accuracy. Empirical testing shows our method is capable of localizing objects 30m from the user with an error of less than 10cm. Finally, we demonstrate a set of techniques that allow a multi-layer perceptron (MLP) to learn resolution-invariant representations of 2D images, including the proposal of an MCMC-based technique to improve the selection of pixels for mini-batches used for training. We also show that a deep convolutional encoder could be trained to output a resolution-independent representation in constant time, and we discuss several potential applications of this research, including image resampling, image compression, and security. Advisors/Committee Members: Michael Gashler, John Gauch, Xintao Wu.

Subjects/Keywords: Computer Vision; Context-aware Computing; Depth-based Positioning; Logical Sensors; Machine Learning; Graphics and Human Computer Interfaces; OS and Networks

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hammer, J. C. (2018). Improving the Efficacy of Context-Aware Applications. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/2703

Chicago Manual of Style (16th Edition):

Hammer, Jon C. “Improving the Efficacy of Context-Aware Applications.” 2018. Doctoral Dissertation, University of Arkansas. Accessed November 26, 2020. https://scholarworks.uark.edu/etd/2703.

MLA Handbook (7th Edition):

Hammer, Jon C. “Improving the Efficacy of Context-Aware Applications.” 2018. Web. 26 Nov 2020.

Vancouver:

Hammer JC. Improving the Efficacy of Context-Aware Applications. [Internet] [Doctoral dissertation]. University of Arkansas; 2018. [cited 2020 Nov 26]. Available from: https://scholarworks.uark.edu/etd/2703.

Council of Science Editors:

Hammer JC. Improving the Efficacy of Context-Aware Applications. [Doctoral Dissertation]. University of Arkansas; 2018. Available from: https://scholarworks.uark.edu/etd/2703

2. Forssén, Per-Erik. Detection of Man-made Objects in Satellite Images.

Degree: The Institute of Technology, 1997, Linköping UniversityLinköping University

In this report, the principles of man-made object detection in satellite images is investigated. An overview of terminology and of how the detection problem is usually solved today is given. A three level system to solve the detection problem is proposed. The main branches of this system handle road, and city detection respectively. To achieve data source flexibility, the Logical Sensor notion is used to model the low level system components. Three Logical Sensors have been implemented and tested on Landsat TM and SPOT XS scenes. These are: BDT (Background Discriminant Transformation) to construct a man-made object property field; Local-orientation for texture estimation and road tracking; Texture estimation using local variance and variance of local orientation. A gradient magnitude measure for road seed generation has also been tested.

Subjects/Keywords: Remote sensing; computer vision; logical sensors; road detection; man-made objects; spectral signature; local variance; quadrature filter; TECHNOLOGY; TEKNIKVETENSKAP

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Forssén, P. (1997). Detection of Man-made Objects in Satellite Images. (Thesis). Linköping UniversityLinköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54356

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Forssén, Per-Erik. “Detection of Man-made Objects in Satellite Images.” 1997. Thesis, Linköping UniversityLinköping University. Accessed November 26, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54356.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Forssén, Per-Erik. “Detection of Man-made Objects in Satellite Images.” 1997. Web. 26 Nov 2020.

Vancouver:

Forssén P. Detection of Man-made Objects in Satellite Images. [Internet] [Thesis]. Linköping UniversityLinköping University; 1997. [cited 2020 Nov 26]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54356.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Forssén P. Detection of Man-made Objects in Satellite Images. [Thesis]. Linköping UniversityLinköping University; 1997. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54356

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.