Using computer vision to gain health insights from social media
Name
1078690125-MIT.pdf
Description
Full printable version
Size
23.33 MB
Format
Adobe PDF
Checksum (MD5)
13fd32f495905152e3b2f0a1e2a4a118
Author(s)
Biswas, Aritro
Advisor(s)
Antonio Torralba.
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
In 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.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 69-71).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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