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Filtering by: Creator Li, Cheng Remove constraint Creator: Li, Cheng Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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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
    Full Text:
    : Visual Object Discovery and Understanding Abstract approved: Fuxin Li Learning to recognize objects is

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Xingyi Li for the degree

  • Investigating Latent State and Uncertainty Representations in Reinforcement Learning

    Creator:
    Koul, Anurag
    Abstract:
    Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
    Resource Type:
    Dissertation
    Full Text:
    show my gratitude to my committee members: Prof. Prasad Tadepalli, Prof. Fuxin Li, and Prof. Weng-Keng

  • Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

    Creator:
    Aziere, Nicolas
    Abstract:
    This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
    Resource Type:
    Dissertation
    Full Text:
    , Tieqiao Wang, Ajay Kr- ishna, Khoi Nguyen and Jun Li. Your perspectives and shared enthusiasm have

  • Object Tracking-by-Segmentation in Videos

    Creator:
    Chen, Sheng
    Abstract:
    This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
    Resource Type:
    Dissertation
    Full Text:
    committee members: Prof. Li, Prof. Niemeyer and Prof. Tadepalli for your precious time. I would like to

  • Assisting Sustainability Analysis of Forest Bioenergy Supply Chains using Mathematical Optimization

    Creator:
    Sadeghi, Javad
    Abstract:
    Changes in the global climate and forest management practices have given rise to increasing numbers and severity of wildfires. More than five million acres burned in the United States in 2017, while in Canada 7.4 million acres burned. In particular, an increasing amount of dead woody biomass is a key...
    Resource Type:
    Masters Thesis

  • Nanoparticle-assisted diffusion brazing of metal microchannel arrays : nanoparticle synthesis, deposition, and characterization

    Creator:
    Eluri, Ravindranadh T.
    Abstract:
    Microchannel process technology (MPT) offers several advantages to the field of nanomanufacturing: 1) improved process control over very short time intervals owing to shorter diffusional distances; and 2) reduced reactor size due to high surface area to volume ratios and enhanced heat and mass transfer. The objective of this thesis...
    Resource Type:
    Dissertation
    Full Text:
    Manufacturing Science and Engineering. 2010;132:030902-5. [9] Zhang Z, Li JC, Jiang Q. Modelling for size

  • Learning with Limited Labeled Data in Natural Language Processing

    Creator:
    Obeidat, Rasha
    Abstract:
    The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
    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

  • Offensive Direction Inference in Real-World Football Video

    Creator:
    Lu, Qingkai
    Abstract:
    Automatic analysis of American football videos can help teams develop strategies and extract patterns with less human effort. In this work, we focus on the problem of automatically determining which team is on offense/defense, which is an important subproblem for higher-level analysis. While seemingly mundane, this problem is quite challenging...
    Resource Type:
    Masters Thesis