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Filtering by: Creator Wu, Ting Remove constraint Creator: Wu, Ting Committee Member Todorovic, Sinisa Remove constraint Committee Member: Todorovic, Sinisa

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  • Visual object discovery and understanding

    Creator:
    Yuan, Jialin
    Abstract:
    Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
    Resource Type:
    Dissertation

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation

  • Towards Annotation-Efficient Video Representation Learning

    Creator:
    Patravali, Jay Sanjay
    Abstract:
    Labeling videos is costly, time-consuming and tedious. These costs can escalate in applications such as medical diagnosis or autonomous driving where we need domain expertise for annotation. Few-shot action recognition aims to solve this problem by annotation-efficient learning mechanisms. This thesis presents MetaUVFS as the first Unsupervised Meta-learning algorithm for...
    Resource Type:
    Masters Thesis

  • Variable selection in semi-parametric models

    Creator:
    Jiang, Shuping
    Abstract:
    We consider two semiparametric regression models for data analysis, the stochastic additive model (SAM) for nonlinear time series data and the additive coefficient model (ACM) for randomly sampled data with nonparametric structure. We employ the SCAD-penalized polynomial spline estimation method for estimation and simultaneous variable selection in both models. It...
    Resource Type:
    Dissertation
    Full Text:
    literature. For example, Chen and Tsay (1993) considered two backfit­ ting techniques: alternating

  • Learning with Partial Supervision for Clustering and Classification

    Creator:
    Pei, Yuanli
    Abstract:
    In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
    Resource Type:
    Dissertation

  • Implementing High Dynamic Range (HDR) Photography to Improve 3D Laser Scanning Point Cloud Visualization and Segmentation

    Creator:
    Mahmoudabadi, Hamid
    Abstract:
    This research explores several novel approaches to improve visualization and segmentation of point clouds acquired with 3D laser scanning. 3D laser scanning is used in a wide variety of applications including surveying and mapping, transportation asset management, facilities management, building information modeling, crime scene investigations, cultural heritage and geologic instigations....
    Resource Type:
    Dissertation

  • Automated Monitoring of Modular Construction Factories using Computer Vision

    Creator:
    Panahi, Roshan
    Abstract:
    Modular construction is increasingly seen as an efficient construction method in terms of time, cost, and energy. The full realization of these advantages partly relies on the efficiency of the production process inside the modular factories, which currently rely on tedious manual monitoring methods or expensive automated techniques. As a...
    Resource Type:
    Dissertation

  • Applied color processing

    Creator:
    Zhang, Heng
    Abstract:
    The quality of a digital image pipeline relies greatly on its color reproduction which should at a minimum handle the color constancy, and the final judgment of the excellence of the pipeline is made through subjective observations by humans. This dissertation addresses a few topics surrounding the color processing of...
    Resource Type:
    Dissertation
    Full Text:
    Cui, Dr. Ting Wu, Dr. Qingwei Li, Dr. Zhenyong Zhang, Mr. Lechun Jin, Mr. Jie Fang, Dr. Lin Wei, Dr

  • Weak-supervision : Probabilistic Models and Inference

    Creator:
    Pham, Anh
    Abstract:
    In supervised learning, label information can be provided at different levels of granularity. For small datasets, it is possible to acquire a label for each data instance. However, in the big-data regime, this fine granularity approach is prohibitively costly. For example, in semi-supervised learning, only a limited number of samples...
    Resource Type:
    Dissertation

  • Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

    Creator:
    Khorram, Saeed
    Abstract:
    The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
    Resource Type:
    Dissertation