Now showing items 1-5 of 5

    • Automatic detection of geospatial objects using multiple hierarchical segmentations 

      Akçay, H. G.; Aksoy, S. (Institute of Electrical and Electronics Engineers, 2008-07)
      The object-based analysis of remotely sensed imagery provides valuable spatial and structural information that is complementary to pixel-based spectral information in classification. In this paper, we present novel methods ...
    • Canlı hücre bölütlemesi için gözeticili öğrenme modeli 

      Koyuncu, Can Fahrettin; Durmaz, İrem; Çetin-Atalay, Rengül; Gündüz-Demir, Çiğdem (IEEE Computer Society, 2014-04)
      Automated cell imaging systems have been proposed for faster and more reliable analysis of biological events at the cellular level. The first step of these systems is usually cell segmentation whose success affects the ...
    • Multi-resolution segmentation and shape analysis for remote sensing image classification 

      Aksoy, Selim; Akçay H. Gökhan (IEEE, 2005-06)
      We present an approach for classification of remotely sensed imagery using spatial information extracted from multi-resolution approximations. The wavelet transform is used to obtain multiple representations of an image ...
    • Tissue object patterns for segmentation in histopathological images 

      Gündüz-Demir, Çiğdem (ACM, 2011)
      In the current practice of medicine, histopathological examination is the gold standard for routine clinical diagnosis and grading of cancer. However, as this examination involves the visual analysis of biopsies, it is ...
    • Unsupervised tissue image segmentation through object-oriented texture 

      Tosun, Akif Burak; Sokmensuer, C.; Gündüz-Demir, Çiğdem (IEEE, 2010)
      This paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use ...