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    Embodied learning for visual recognition

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    JAYARAMAN-DISSERTATION-2017.pdf (24.01Mb)
    Date
    2017-08-10
    Author
    Jayaraman, Dinesh
    0000-0002-6888-3095
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    Abstract
    The field of visual recognition in recent years has come to rely on large expensively curated and manually labeled "bags of disembodied images". In the wake of this, my focus has been on understanding and exploiting alternate "free" sources of supervision available to visual learning agents that are situated within real environments. For example, even simply moving from orderless image collections to continuous visual observations offers opportunities to understand the dynamics and other physical properties of the visual world. Further, embodied agents may have the abilities to move around their environment and/or effect changes within it, in which case these abilities offer new means to acquire useful supervision. In this dissertation, I present my work along this and related directions.
    Department
    Electrical and Computer Engineering
    Subject
    Computer vision
    Unsupervised learning
    Embodied learning
    URI
    http://hdl.handle.net/2152/63489
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