Age and gender have been extracted using the entropy, Ridge to Valley Area (RVA) and neural-based training of the energies of fingerprints using haar wavelet transform. Gender has been proposed based on fingerprint entropy. The age has been estimated using the energies of the fingerprint computed up to 3rd level of the haar wavelet. It is proposed to decompose the fingerprint at level 3 thereby computing the 12 numbers of energy levels. These energy levels along with RVA and entropy are made as input neurons to a back propagation neural network with two hidden neurons and four output classes. The back propagation neural network is trained using 300 samples of fingerprint images with 150 male and 150 female images. The weights are adjusted with a target MSE of 0.00001. The neural network is trained at a learning rate of 0.1, thereby giving fast learning of the network with weights adjusted to tune the four output classes i.e. 10-15, 16-20, 21-25, and 26-30 age groups.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Age and gender have been extracted using the entropy, Ridge to Valley Area (RVA) and neural-based training of the energies of fingerprints using haar wavelet transform. Gender has been proposed based on fingerprint entropy. The age has been estimated using the energies of the fingerprint computed up to 3rd level of the haar wavelet. It is proposed to decompose the fingerprint at level 3 thereby computing the 12 numbers of energy levels. These energy levels along with RVA and entropy are made as input neurons to a back propagation neural network with two hidden neurons and four output classes. The back propagation neural network is trained using 300 samples of fingerprint images with 150 male and 150 female images. The weights are adjusted with a target MSE of 0.00001. The neural network is trained at a learning rate of 0.1, thereby giving fast learning of the network with weights adjusted to tune the four output classes i.e. 10-15, 16-20, 21-25, and 26-30 age groups. 72 pp. Englisch. N° de réf. du vendeur 9786205511756
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Age and gender have been extracted using the entropy, Ridge to Valley Area (RVA) and neural-based training of the energies of fingerprints using haar wavelet transform. Gender has been proposed based on fingerprint entropy. The age has been estimated using the energies of the fingerprint computed up to 3rd level of the haar wavelet. It is proposed to decompose the fingerprint at level 3 thereby computing the 12 numbers of energy levels. These energy levels along with RVA and entropy are made as input neurons to a back propagation neural network with two hidden neurons and four output classes. The back propagation neural network is trained using 300 samples of fingerprint images with 150 male and 150 female images. The weights are adjusted with a target MSE of 0.00001. The neural network is trained at a learning rate of 0.1, thereby giving fast learning of the network with weights adjusted to tune the four output classes i.e. 10-15, 16-20, 21-25, and 26-30 age groups. N° de réf. du vendeur 9786205511756
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Wadhwa RaviMr. Ravi Wadhwa has 15 years of experience in research and academics. He works in various positions in different positions. He is presently working at Chandigarh University, Mohali, India. He serves the university as Assit. N° de réf. du vendeur 755870550
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Age and gender have been extracted using the entropy, Ridge to Valley Area (RVA) and neural-based training of the energies of fingerprints using haar wavelet transform. Gender has been proposed based on fingerprint entropy. The age has been estimated using the energies of the fingerprint computed up to 3rd level of the haar wavelet. It is proposed to decompose the fingerprint at level 3 thereby computing the 12 numbers of energy levels. These energy levels along with RVA and entropy are made as input neurons to a back propagation neural network with two hidden neurons and four output classes. The back propagation neural network is trained using 300 samples of fingerprint images with 150 male and 150 female images. The weights are adjusted with a target MSE of 0.00001. The neural network is trained at a learning rate of 0.1, thereby giving fast learning of the network with weights adjusted to tune the four output classes i.e. 10-15, 16-20, 21-25, and 26-30 age groups.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. N° de réf. du vendeur 9786205511756
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Age and Gender Estimation from Fingerprint Images | Entropy Ridge to Valley Area and Back Propagation Neural Network | Ravi Wadhwa (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786205511756 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 125816438
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