Search Constraints

Start Over
Filtering by: Creator Kass, David Remove constraint Creator: Kass, David Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

Search Results

  • Object highlighting : real-time boundary detection using a Bayesian network

    Creator:
    Jia, Jin
    Abstract:
    Image segmentation continues to be a fundamental problem in computer vision and image understanding. In this thesis, we present a Bayesian network that we use for object boundary detection in which the MPE (most probable explanation) before any evidence can produce multiple non-overlapping, non-self-intersecting closed contours and the MPE with...
    Resource Type:
    Masters Thesis
    Full Text:
    thank Professor Ron Metoyer, Professor Prasad Tadepalli and Professor David Birkes for being on my

  • Probabilistic models for classification of bioacoustic data

    Creator:
    Lakshminarayanan, Balaji
    Abstract:
    Probabilistic models have been successfully applied for a wide variety of problems, such as but not limited to information retrieval, computer vision, bio-informatics and speech processing. Probabilistic models allow us to encode our assumptions about the data in an elegant fashion and enable us to perform machine learning tasks such...
    Resource Type:
    Masters Thesis

  • Involving older adults in the design and development of free/open source software

    Creator:
    Davidson, Jennifer L.
    Abstract:
    An age-wave is upon us where many older adults are reaching retirement. Technically experienced older adults have skills that could be directly applied to free/open source software (FOSS) communities, such as project management, programming, and/or knowledge of a rapidly growing end-user population. FOSS is a widely popular, low-cost way to...
    Resource Type:
    Dissertation
    Full Text:
     Research  Network,  Rochester,  NY,  2004. 4. David,   P., Watermann,   A.,   and Arora,   S.   FLOSS

  • 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