Now showing items 1-5 of 5

    • Automated Remote Sensing Image Interpretation with Limited Labeled Training Data 

      Li, Fan (University of Waterloo, 2015-08-24)
      Automated remote sensing image interpretation has been investigated for more than a decade. In early years, most work was based on the assumption that there are sufficient labeled samples to be used for training. However, ...
    • Diabetic retinopathy grading with respect to the segmented lesions 

      Kheradfallah, Hoda (University of Waterloo, 2022-05-19)
      One of the leading causes of irreversible vision loss is Diabetic Retinopathy (DR). The International Clinical Diabetic Retinopathy scale (ICDRS) provides grading criteria for DR. Deep Convolutional Neural Networks (DCNNs) ...
    • A New Look Into Image Classification: Bootstrap Approach 

      Ochilov, Shuhratchon (University of Waterloo, 2012-03-15)
      Scene classification is performed on countless remote sensing images in support of operational activities. Automating this process is preferable since manual pixel-level classification is not feasible for large scenes. ...
    • Segmentation of RADARSAT-2 Dual-Polarization Sea Ice Imagery 

      Yu, Peter (University of Waterloo, 2009-09-24)
      The mapping of sea ice is an important task for understanding global climate and for safe shipping. Currently, sea ice maps are created by human analysts with the help of remote sensing imagery, including synthetic aperture ...
    • Statistical Model-Based Corneal Reconstruction 

      Eichel, Justin (University of Waterloo, 2013-12-10)
      Precise measurements of corneal layer thickness are required to treat, evaluate risk of, and determine the progression of pathologies within the eye. The thickness measurements are typically acquired as 2d images, known ...


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