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University of Washington

1. Seeds, Christopher Edward. Seen / Unseen: How humans and machines process our everyday photos.

Degree: 2018, University of Washington

This thesis researches the contrasting ways in which humans and machines view everyday photographs. Different ways of “seeing” photographs are explored through three unique prototypes. Each prototype looks at different capabilities that are unique to humans or to machines. The intention of this project is to create a heightened awareness of the importance of human involvement with machines. Advisors/Committee Members: Matthews, Kristine (advisor).

Subjects/Keywords: Design; Interaction Design; Memory; Design; Design

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

APA (6th Edition):

Seeds, C. E. (2018). Seen / Unseen: How humans and machines process our everyday photos. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/42160

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):

Seeds, Christopher Edward. “Seen / Unseen: How humans and machines process our everyday photos.” 2018. Thesis, University of Washington. Accessed October 19, 2018. http://hdl.handle.net/1773/42160.

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

MLA Handbook (7th Edition):

Seeds, Christopher Edward. “Seen / Unseen: How humans and machines process our everyday photos.” 2018. Web. 19 Oct 2018.

Vancouver:

Seeds CE. Seen / Unseen: How humans and machines process our everyday photos. [Internet] [Thesis]. University of Washington; 2018. [cited 2018 Oct 19]. Available from: http://hdl.handle.net/1773/42160.

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

Council of Science Editors:

Seeds CE. Seen / Unseen: How humans and machines process our everyday photos. [Thesis]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/42160

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

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