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https://hdl.handle.net/20.500.14279/2545| Title: | Texture classification using ART-based neural networks and fractals | Authors: | Kasparis, Takis Charalampidis, Dimitrios Georgiopoulos, Michael N. |
metadata.dc.contributor.other: | Κασπαρής, Τάκης | Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Classification;Fractals;Computer vision;Neural networks | Issue Date: | 17-Jul-1998 | Source: | Signal Processing, Sensor Fusion, and Target Recognition VII, 1998, Orlando, Florida | Conference: | SPIE Conference Proceedings | Abstract: | In this paper texture classification is studied based on the fractal dimension (FD) of filtered versions of the image and the Fuzzy ART Map neural network (FAMNN). FD is used because it has shown good tolerance to some image transformations. We implemented a variation of the testing phase of Fuzzy ARTMAP that exhibited superior performance than the standard Fuzzy ARTMAP and the 1-nearest neighbor (1-NN) in the presence of noise. The performance of the above techniques is tested with respect to segmentation of images that include more than one texture. | Description: | Part of Artificial Intelligence Applications and Innovations | ISBN: | 978-3-642-41142-7 | ISSN: | 0277-786X 2-s2.0-84894100156 https://api.elsevier.com/content/abstract/scopus_id/84894100156 |
DOI: | 10.1117/12.327099 | Rights: | © 1998 Spie | Type: | Conference Papers | Affiliation: | University of Central Florida | Affiliation : | University of Central Florida |
| Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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