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dc.contributor.advisorAntonio Torralba.en_US
dc.contributor.authorBiswas, Aritroen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-12-18T19:48:17Z
dc.date.available2018-12-18T19:48:17Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/119746
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.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.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 69-71).en_US
dc.description.abstractIn this thesis, I developed machine learning methods that would support tools for gaining health insights from social media images. On the one hand, I have helped create a dataset for food image segmentation and a segmentation network for this task, a task that is very relevant for understanding the nutritional content of food from images. I also explored the flip side of the issue, and helped design an interface that users can use to explore food recipes in machine learning-driven ways. On the other hand, I helped create a dataset and model for classifying types of disasters given images of natural or manmade disasters.en_US
dc.description.statementofresponsibilityby Aritro Biswas.en_US
dc.format.extent71 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleUsing computer vision to gain health insights from social mediaen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1078690125en_US


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