Image segmentation applications with unsupervised neural networks - Şengür, Abdulkadir; Türko?lu, Ibrahim; Ince, M. Cevdet (My University, 2005)
Image segmentation is the most difficult task of low level computer vision applications. The performance of the segmentation algorithm affects the subsequent applications performances such as high level pattern recognition applications. In this study we examine 1-D and 2-D unsupervised artificial neural networks (Kohonen network) and we evaluate the performances of the examined structures over image segmentation applications. Experimental studies show the advantages and disadvantages of the Kohonen networks. © 2005 IEEE.
E?iticisiz yapay sinir aglari ile görüntü bölütleme uygulamalari
IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005 -- 16 May 2005 through 18 May 2005 -- Kayseri -- 69003
Keywords: Algorithms; Computer vision; Image segmentation; Pattern recognition; Segmentation algorithms; Neural networks