Isbn: 9783843391184 - fuzzy lattice neural model and fuzzy equivalance relation model: classification and clustering (9 risultati)

Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2011
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Condizione: New. pp. 132.

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Taschenbuch. Condizione: Neu. Fuzzy Lattice Neural Model and Fuzzy Equivalance Relation Model | Classification and Clustering | Kalamani Duraisamy | Taschenbuch | 132 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783843391184 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computer vision, unlike humans, still has not fully acquired the ability to categorise a person's age group from an image of the person's face. Successful gender and age classification could be used to boot the performance of face recognition system. Fuzzy models have been used and analysed in this work to achieve the desired results. The concept of fuzzy lattice neural model is introduced and is applied to classify the age group of a person from the gray scale facial image. Next, the fuzzy equivalence relation model is constructed and is used to classify the age group of a person. Then, the fuzzy lattice neural model is applied to segment an aerial gray scale image. Finally, fuzzy lattice neural model is compared with other models like fuzzy equivalence relation model, Kohenen's clustering neural model that are used for classification. The hybridization of the technologies is demonstrated on architectures such as Neuro-fuzzy systems. This book should be of interest to researchers and technologists desirous of applying FLN technology to their respective fields of work. 132 pp. Englisch.…

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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Computer vision, unlike humans, still has not fully acquired the ability to categorise a person's age group from an image of the person's face. Successful gender and age classification could be used to boot the performance of face recognition system. Fuzzy models have been used and analysed in this work to achieve the desired results. The concept of fuzzy lattice neural model is introduced and is applied to classify the age group of a person from the gray scale facial image. Next, the fuzzy equivalence relation model is constructed and is used to classify the age group of a person. Then, the fuzzy lattice neural model is applied to segment an aerial gray scale image. Finally, fuzzy lattice neural model is compared with other models like fuzzy equivalence relation model, Kohenen's clustering neural model that are used for classification. The hybridization of the technologies is demonstrated on architectures such as Neuro-fuzzy systems. This book should be of interest to researchers and technologists desirous of applying FLN technology to their respective fields of work.…

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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: DURAISAMY KALAMANID.Kalamani is Associate Professor, Department of Mathematics at the Kongu Engineering College, Erode, Tamilnadu, India. She is a a gold medalist from Bharathiar University. She has over 15 years of teaching exper.…

Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2011
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Condizione: New. Print on Demand pp. 132 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Lingua: Inglese
Editore: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2011
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 132.

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computer vision, unlike humans, still has not fully acquired the ability to categorise a person''s age group from an image of the person''s face. Successful gender and age classification could be used to boot the performance of face recognition system. Fuzzy models have been used and analysed in this work to achieve the desired results. The concept of fuzzy lattice neural model is introduced and is applied to classify the age group of a person from the gray scale facial image. Next, the fuzzy equivalence relation model is constructed and is used to classify the age group of a person. Then, the fuzzy lattice neural model is applied to segment an aerial gray scale image. Finally, fuzzy lattice neural model is compared with other models like fuzzy equivalence relation model, Kohenen''s clustering neural model that are used for classification. The hybridization of the technologies is demonstrated on architectures such as Neuro-fuzzy systems. This book should be of interest to researchers and technologists desirous of applying FLN technology to their respective fields of work.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch.…