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  • A probabilistic model for anomaly detection in remote sensor streams

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access. Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial...
    Resource Type:
    Masters Thesis
    Full Text:
    Computer Science presented on October 25th, 2007. Title: A Probabilistic Model for Anomaly Detection in

  • Three methods for estimating subpixel cover fractions in coarse resolution imagery

    Creator:
    Damon, Diane L.
    Abstract:
    Coarse resolution imagery, such as that produced by the MODIS instrument, poses the challenge of estimating sub-pixel proportions of di erent land cover types. This problem is di cult because of the variety and variability of vegetation within individual pixels. This thesis describes and compares two existing algorithms for estimating...
    Resource Type:
    Masters Thesis
    Full Text:
    are the linear spectral mixture model, which has previously been applied to coarse-resolution imagery

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    subgraphs. After finding the workflow models, we create a Logical Hidden Markov Model (LHMM) for each mined

  • Image feature detection and matching for biological object recognition

    Creator:
    Deng, Hongli
    Abstract:
    Image feature detection and matching are two critical processes for many computer vision tasks. Currently, intensity-based local interest region detectors and local feature-based matching methods are used widely in computer vision applications. But in some applications, such as biological object recognition tasks, within-class changes in pose, lighting, color, and texture...
    Resource Type:
    Dissertation
    Full Text:
    . 6.2 and 6.12. . . . . . . . . . 106 7.1 Various types of spatial models. (a) Constellation model. (b

  • 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:
    classification model for the learning problem. The thesis also analyzes the learnability of the superset label