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http://hdl.handle.net/10397/6044
Title: | Modular expert network approach to histogram thresholding | Authors: | Li, CH Tam, PKS |
Issue Date: | Jul-1997 | Source: | Journal of electronic imaging, July 1997, v. 6, no. 3, p. 286-293 | Abstract: | The problem of histogram thresholding is tackled using a modular expert network. The modular expert network is a network of expert modules modulated by a gating network. The expert modules incorporate individual experts' opinions on the thresholding problem. The difficult task of integration of conflicting experts' opinions is achieved through a training of the gating network using backpropagation. The resulting network achieves accurate modeling of the solution mapping through the efficient combination of existing experts. Experimental results show the superior performance of the modular network over classical algorithms. In particular, a near-optimal solution was shown to be achievable using a small training set. Application to a real-world biomedical cell segmentation problem is also given. | Keywords: | Backpropagation Cellular biophysics Feedforward neural nets Image segmentation Medical expert systems Medical image processing Modules Neural net architecture Statistical analysis |
Publisher: | SPIE-International Society for Optical Engineering | Journal: | Journal of electronic imaging | ISSN: | 1017-9909 | EISSN: | 1560-229X | DOI: | 10.1117/12.269904 | Rights: | Chun Hung Li and Peter K. S. Tam, "Modular expert network approach to histogram thresholding," J. Electron. Imaging., 6(3), p. 286-293 (1997) Copyright 1997 Society of Photo-Optical Instrumentation Engineers & Society for Imaging Science and Technology. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. http://dx.doi.org/10.1117/12.269904 |
Appears in Collections: | Journal/Magazine Article |
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