@InProceedings{FernandesNavaFich:2001:SeTEIm,
               author = "Fernandes, D{\^e}nis and Navaux, Philippe Olivier Alexandre and 
                         Fichtner, Paulo Fernando Papaleo",
                title = "Segmentation of TEM images using oscillatory neural networks",
            booktitle = "Proceedings...",
                 year = "2001",
               editor = "Borges, Leandro D{\'{\i}}bio and Wu, Shin-Ting",
                pages = "289--296",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 14. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
                 note = "The conference was held in Florian{\'o}polis, SC, Brazil, from 
                         October 15 to 18.",
             keywords = "mage segmentation, oscillatory networks, neural networks.",
             abstract = "Oscillatory neural networks are a relatively recent approach for 
                         the problem of image segmentation. Inside of this context, the 
                         oscillator neuron of Terman-Wang is presented, which one is used 
                         as base element of an oscillatory network called LEGION (Locally 
                         Excitatory Globally Inhibitory Oscillator Network). The continuous 
                         version of the LEGION network, based on a set of differential 
                         equations, presents high computational complexity and has limited 
                         capacity of segmentation, what restricts its practical 
                         application, being adequate for implementation in parallel 
                         hardware topologies. To reduce the computational complexity in 
                         serial computers, an algorithm proposed by Terman and Wang is 
                         presented, which implies significant gain of speed in comparison 
                         to the continuous version and, in contrast, capacity to 
                         discriminate a unlimited number of segments.An interactive version 
                         of this algorithm was proposed and the results obtained in 
                         segmentation of transmission electron microscopy (TEM) images were 
                         evaluated, with the objective of obtaining measures of helium 
                         bubbles in silicon samples. As final result we found that the 
                         LEGION network presents itself as a singular alternative to solve 
                         problems of image segmentation, which provides simultaneously both 
                         spatial and temporal discrimination of segments.",
  conference-location = "Florian{\'o}polis, SC, Brazil",
      conference-year = "15-18 Oct. 2001",
                  doi = "10.1109/SIBGRAPI.2001.963068",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2001.963068",
             language = "en",
         organisation = "SBC - Brazilian Computer Society",
                  ibi = "6qtX3pFwXQZeBBx/wmcRB",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZeBBx/wmcRB",
           targetfile = "289-296.pdf",
        urlaccessdate = "2024, May 02"
}