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Filtering by: Creator Su, Yi-Hsuan Remove constraint Creator: Su, Yi-Hsuan Committee Member Raich, Raviv Remove constraint Committee Member: Raich, Raviv Degree Field Computer Science Remove constraint Degree Field: Computer Science

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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:
    et al., 2021, Su et al., 2019]. These models are designed to process and generate information from

  • 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:
    Gaussian random vectors in Rd such that for every i, j, E|Yi − Yj |2 ≤ E|Xi −Xj |2 (2.7) then for every

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation
    Full Text:
    : Tianfu Wu, Zhenyu Yao, Jiangen Zhang, Xiaohan Nie, Bo Li, Xi Song and Yi Xie. Last but not least, I

  • 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
    Full Text:
    Pairwise Constraints: the values of Q̃(lpj |yi = k, I p j ), i ∈ I p j . For simplicity, we denote q·k

  • Multi-instance multi-label learning : algorithms and applications to bird bioacoustics

    Creator:
    Briggs, Forrest
    Abstract:
    We consider the problem of supervised classification of bird species from audio recordings in a real-world acoustic monitoring scenario (i.e. audio data is collected in the field with an omnidirectional microphone, without human supervision). Obtaining better data about bird activity can assist conservation efforts, and improve our understanding of their...
    Resource Type:
    Dissertation
    Full Text:
    signal processing methods are not su�cient for the HJA audio dataset because they do not handle

  • Algorithms for massive biological datasets

    Creator:
    Bryant, Douglas W. (Douglas Wesley)
    Abstract:
    Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
    Resource Type:
    Dissertation
    Full Text:
    , each iteration of contig extension (line 22) is contingent on there existing su�ciently many matching

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    -label (MIML) formulation [78], the training data consist of pairs (Bi, Yi), where Bi = {xi,1, . . . ,xi

  • Anomaly Detection: Theory, Explanation and User Feedback

    Creator:
    Siddiqui, Md Amran
    Abstract:
    Anomaly detection has been used in variety of applications in practice, including cyber-security, fraud detection and detecting faults in safety critical systems, etc. Anomaly detectors produce a ranked list of statistical anomalies, which are typically examined by human analysts in order to extract the actual anomalies of interest. Unfortunately, most...
    Resource Type:
    Dissertation
    Full Text:
    application domain. One way to align the statistical measure to the target behavior is via some su