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https://hdl.handle.net/20.500.14279/2494
Πεδίο DC | Τιμή | Γλώσσα |
---|---|---|
dc.contributor.author | Kasparis, Takis | - |
dc.contributor.author | Eichmann, George | - |
dc.contributor.author | Georgiopoulos, Michael N. | - |
dc.date.accessioned | 2013-02-19T10:35:45Z | en |
dc.date.accessioned | 2013-05-17T05:30:09Z | - |
dc.date.accessioned | 2015-12-02T11:27:22Z | - |
dc.date.available | 2013-02-19T10:35:45Z | en |
dc.date.available | 2013-05-17T05:30:09Z | - |
dc.date.available | 2015-12-02T11:27:22Z | - |
dc.date.issued | 1990-09-01 | - |
dc.identifier.citation | Hybrid Image and Signal Processing II; (1990), vol.1297, Technical Symposium on Optics, Electro-Optics, and Sensors, Orlando, FL, United States | en_US |
dc.identifier.issn | 0277-786X | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/2494 | - |
dc.description.abstract | The ability to classify texture regions in images is considered to be an important aspect of scene analysis. The information gained from such classification can be used by a computer vision system to assist in image segmentation as well as object identification. In this paper, the use of a neural network model in performing classification of images containing regular textures is investigated. The texture features used in the classification process are Hough transform-based descriptors. The performance and capabilities of the neural network approach are then compared to classical technique utilizing a linear associative memory. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.rights | © 1990 SPIE | en_US |
dc.subject | Image processing | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Pattern recognition | en_US |
dc.title | Image pattern algorithms using neural networks | en_US |
dc.type | Conference Papers | en_US |
dc.collaboration | University of Central Florida | en_US |
dc.collaboration | The City College of New York | en_US |
dc.subject.category | Electrical Engineering - Electronic Engineering - Information Engineering | en_US |
dc.country | United States | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.relation.conference | SPIE Conference Proceedings | en_US |
dc.identifier.doi | 10.1117/12.21323 | en_US |
dc.dept.handle | 123456789/54 | en |
cut.common.academicyear | 2019-2020 | en_US |
item.fulltext | No Fulltext | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.cerifentitytype | Publications | - |
item.openairetype | conferenceObject | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-3486-538x | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Εμφανίζεται στις συλλογές: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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