DocumentCode
2648633
Title
Neural techniques for image segmentation
Author
Marsella, Marco ; Miranda, Sergio
Author_Institution
Dipartimento di Ingegneria dell´´Inf. e Matematica Appl., Salerno Univ., Italy
fYear
1998
fDate
21-23 May 1998
Firstpage
367
Lastpage
372
Abstract
We present new neural techniques including unsupervised technology and fuzzy logic foundations. We realized a hybrid neural network and applied three different unsupervised learning algorithms that we developed specially for it: fuzzy MLSOM, fuzzy hierarchical “neural gas” and fuzzy hierarchical “maximum entropy”. The experiments presented deal with image segmentation. The results obtained show that neural networks are a valid instrument for image processing and shape recognition
Keywords
computer vision; fuzzy neural nets; image recognition; image segmentation; self-organising feature maps; unsupervised learning; fuzzy MLSOM; fuzzy hierarchical maximum entropy; fuzzy logic; fuzzy neural networks; image segmentation; shape recognition; unsupervised learning; Artificial neural networks; Entropy; Fuzzy logic; Fuzzy neural networks; Image processing; Image segmentation; Instruments; Neural networks; Neurons; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligence and Systems, 1998. Proceedings., IEEE International Joint Symposia on
Conference_Location
Rockville, MD
Print_ISBN
0-8186-8548-4
Type
conf
DOI
10.1109/IJSIS.1998.685477
Filename
685477
Link To Document