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ThesisV.10(revisions).pdf (16.33 MB)

ETD Abstract Container

Abstract Header

Artificial Attention: Baseline Behavior

Roberts, Daniel
http://rave.ohiolink.edu/etdc/view?acc_num=osu1367572518

Abstract Details

, Master of Science, Ohio State University, Industrial and Systems Engineering.
Computational attention models have not been fully exploited in their potential for exploring a world and mitigating data overload. This research explores high-level concepts that could increase the capabilities of all models. We propose promoting the ability of the software to manipulate the sensors they are analyzing, the creation of a highly flexible saliency map construction method, and the introduction of temporal dependencies to create a dynamic and persistent search behavior that is capable of effectively exploring the world while simultaneously focusing on particular features. We do this through the creation and testing of an algorithm called Artificial Attention (Woods and Morison, 2012).
David Woods (Advisor)
Phillip Smith (Committee Member)
Computer Science; Remote Sensing

Recommended Citations

Citations

  • Roberts, D. (n.d.). Artificial Attention: Baseline Behavior [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1367572518

    APA Style (7th edition)

  • Roberts, Daniel. Artificial Attention: Baseline Behavior. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1367572518.

    MLA Style (8th edition)

  • Roberts, Daniel. "Artificial Attention: Baseline Behavior." Master's thesis, Ohio State University. Accessed APRIL 19, 2024. http://rave.ohiolink.edu/etdc/view?acc_num=osu1367572518

    Chicago Manual of Style (17th edition)

osu1367572518
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