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Filtering by: Creator Mroczek, Daniel K. Remove constraint Creator: Mroczek, Daniel K. Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan Committee Member Li, Fuxin Remove constraint Committee Member: Li, Fuxin

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  • Fine-Grained Object Recognition Under Limited Training Data

    Creator:
    Lam, Michael Q.
    Abstract:
    This dissertation addresses object recognition in challenging settings, where distinct object classes are visually very similar (e.g., species of birds and insects) and/or access to training examples of object classes is limited (e.g., due to the associated high costs of data annotation). In this dissertation, we present a variety of...
    Resource Type:
    Dissertation
    Full Text:
    1...K: ψunary(x,y)= [ ∑ni=1 I(yi = 1)φ(xi) , . . . , ∑ni=1 I(yi =K)φ(xi) ] . In the Nematocyst

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    , where k is the number of view types. Specifically, for a year of data with 4 view types and 20-day

  • Data-Driven Approaches For Decoding Volitional Movement Intent From Bioelectrical Signals

    Creator:
    Cunha Dantas, Henrique
    Abstract:
    There are nearly two million limb amputees living in the United States of America. Loss of limbs results in profound changes in one's life. However, the underlying neural circuitry and much of the ability to sense and control movements of their missing limb is retained even after limb loss. This...
    Resource Type:
    Dissertation
    Full Text:
    my queries. At the end, I also thank all of my friends (Lucas, Mauro, Alexandre, Daniel Goes, Joao

  • Robust and Efficient Classification of Videos in the Wild

    Creator:
    Mahasseni, Behrooz
    Abstract:
    Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
    Resource Type:
    Dissertation
    Full Text:
    deformable parts model (DPM) [33]. DPM has K nodes representing K action parts, connected in a star

  • Semantic embodied navigation : developing agents that navigate from language and vision

    Creator:
    Krantz, Jacob
    Abstract:
    Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
    Resource Type:
    Dissertation

  • Part-based and Uncertainty-Aware Few-shot Object Segmentation in Images

    Creator:
    Nguyen, Khoi D.
    Abstract:
    This dissertation addresses few-shot object segmentation in images. The goal of segmentation is to label every image pixel with a class of the object occupying that pixel, where the class may represent a semantic object category or instance. In few-shot segmentation, training and test datasets have different classes. Every new...
    Resource Type:
    Dissertation
    Full Text:
    Boosting . . . . . . . . . . . . . . . . . . . . 43 4.3.3 K-shot Setting

  • A Deep Action Segmentation and Its Explanation with a Dictionary of Meaningful Attention Maps

    Creator:
    Trigkakis, Dimitrios
    Abstract:
    This thesis addresses the problem of temporal action segmentation in videos, where the goal is to label every video frame with the appropriate action class present. We focus on the domain of NFL football videos, where action classes represent common football play types. For action segmentation, we use a temporal...
    Resource Type:
    Masters Thesis
    Full Text:
    the representations for all attention maps, we perform a k-means clustering procedure to produce