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dc.contributor.advisorAude Oliva.en_US
dc.contributor.authorZhao, Anthony Dongen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2016-01-04T19:58:33Z
dc.date.available2016-01-04T19:58:33Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/100611
dc.descriptionThesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionTitle as it appears in MIT Commencement Exercises program, June 5, 2015: Metamers in memory: predicting pairwise image confusions with deep learning. Cataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 81-83).en_US
dc.description.abstractPrevious experiments have examined what causes images to be remembered or forgotten. In these experiments, participants sometimes create false positives when identifying images they have seen before, but the precise cause of these false positives has remained unclear. We examine confusions between individual images as a possible cause of these false positives. We first introduce a new experimental task for examining measuring the rates at which participants confuse one image for another and show that the images prone to false positives are also ones that people tend to confuse. Second, we show that there is a correlation between how often people confuse pairs of images and how similar they find those pairs. Finally, we train a Siamese neural network to predict confusions between pairs of images. By studying the mechanisms behind the failures of memory, we hope to increase our understanding of memory as a whole and move closer to a computational model of memory.en_US
dc.description.statementofresponsibilityby Anthony Dong Zhao.en_US
dc.format.extent83 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleModeling image-to-image confusions in memoryen_US
dc.title.alternativeMetamers in memory : predicting pairwise image confusions with deep learningen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Computer Science and Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc932618780en_US


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