Omar ezz (8 risultati)
- Brossura
Da: Books Puddle, New York, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 63,85
EUR 3,46 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New.
- Brossura
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 36,25
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Gender Detection | Classification Face male/female using multi databases | Ezz Omar (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204182810 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de… | Anbieter: preigu.
- Brossura
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Today's machine learning is widely used in diverse areas. For example, fraudulent systems, recommended systems, exploited prediction, and many other applications. One of these applications, is being exploited in this search. This p…aper presents an approach to detecting a person's gender through the front face image by using extraction features and classification techniques. Gender prediction can be a very useful method in HCI (Human Computer Interaction) systems. As a very powerful method of extracting data, the classification is used here to collect class data and to classify the gender as either male or female. To extract data features, Local Binary Pattern (LBP) is used, whereas the Random Forest (RF) algorithm of classification is used to gauge the maximum accuracy. Various database models were used in this search: ORL database, FEI database, Jaffe database, and CUHK database where JAFFE database gave a very high level of accuracy which is 99.89% in contrast CUHK database which gave a lower level of accuracy 76.18% with relative stability. Details of the prediction model and results model are reported in this paper. 80 pp. Englisch.
- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 63,02
EUR 7,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 63,50
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,25
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Omar EzzMaster s degree in Computer Science with a specialization in Artificial Intelligence.Today s machine learning is widely used in diverse areas. For example, fraudulent systems, recommended syste…ms, exploited prediction, .
- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Today's machine learning is widely used in diverse areas. For example, fraudulent systems, recommended systems, exploited prediction, and many other applications. One of these applications, is being exploited in this search. This paper… presents an approach to detecting a person's gender through the front face image by using extraction features and classification techniques. Gender prediction can be a very useful method in HCI (Human Computer Interaction) systems. As a very powerful method of extracting data, the classification is used here to collect class data and to classify the gender as either male or female. To extract data features, Local Binary Pattern (LBP) is used, whereas the Random Forest (RF) algorithm of classification is used to gauge the maximum accuracy. Various database models were used in this search: ORL database, FEI database, Jaffe database, and CUHK database where JAFFE database gave a very high level of accuracy which is 99.89% in contrast CUHK database which gave a lower level of accuracy 76.18% with relative stability. Details of the prediction model and results model are reported in this paper.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch.
- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 40,89
EUR 60,69 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Today's machine learning is widely used in diverse areas. For example, fraudulent systems, recommended systems, exploited prediction, and many other applications. One of these applications, is being exploited in this search. This paper…presents an approach to detecting a person's gender through the front face image by using extraction features and classification techniques. Gender prediction can be a very useful method in HCI (Human Computer Interaction) systems. As a very powerful method of extracting data, the classification is used here to collect class data and to classify the gender as either male or female. To extract data features, Local Binary Pattern (LBP) is used, whereas the Random Forest (RF) algorithm of classification is used to gauge the maximum accuracy. Various database models were used in this search: ORL database, FEI database, Jaffe database, and CUHK database where JAFFE database gave a very high level of accuracy which is 99.89% in contrast CUHK database which gave a lower level of accuracy 76.18% with relative stability. Details of the prediction model and results model are reported in this paper.
