Instead of learning the specific aging pattern for each person, it is possible to learn the common pattern of aging for more than one person at different ages. For each age, more than one facial image is used for age representation. Each person can have several face images in one age or in an age range. Therefore, this model is more flexible than AGES model, and it is much easier to collect a larger number of samples (facial images) and create a larger database. This model uses a manifold embedding technique for learning a low-dimensional aging trend for many facial images of the same age. The only requirement of this model is that the sample size for learning is large enough so that embedded manifold can be taught with statistical sufficiency. The main objective of this book is to estimate age from different facial features. • To detect face parts like eyes, nose, mouth, chin etc.• To extract facial features of the input face image.• To estimate age by using the extracted features of face.
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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 -Instead of learning the specific aging pattern for each person, it is possible to learn the common pattern of aging for more than one person at different ages. For each age, more than one facial image is used for age representation. Each person can have several face images in one age or in an age range. Therefore, this model is more flexible than AGES model, and it is much easier to collect a larger number of samples (facial images) and create a larger database. This model uses a manifold embedding technique for learning a low-dimensional aging trend for many facial images of the same age. The only requirement of this model is that the sample size for learning is large enough so that embedded manifold can be taught with statistical sufficiency. The main objective of this book is to estimate age from different facial features. - To detect face parts like eyes, nose, mouth, chin etc.- To extract facial features of the input face image.- To estimate age by using the extracted features of face. 68 pp. Englisch. N° de réf. du vendeur 9786202554121
Quantité disponible : 2 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Instead of learning the specific aging pattern for each person, it is possible to learn the common pattern of aging for more than one person at different ages. For each age, more than one facial image is used for age representation. Each person can have several face images in one age or in an age range. Therefore, this model is more flexible than AGES model, and it is much easier to collect a larger number of samples (facial images) and create a larger database. This model uses a manifold embedding technique for learning a low-dimensional aging trend for many facial images of the same age. The only requirement of this model is that the sample size for learning is large enough so that embedded manifold can be taught with statistical sufficiency. The main objective of this book is to estimate age from different facial features. - To detect face parts like eyes, nose, mouth, chin etc.- To extract facial features of the input face image.- To estimate age by using the extracted features of face. N° de réf. du vendeur 9786202554121
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Karande KailashKarande Kailash Jagannath has completed his PhD in Electronics and Telecommunication from SRTM University. He has total 100+ Publications in International and National Journals and Conferences. He has 6 books in his cr. N° de réf. du vendeur 385947214
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Instead of learning the specific aging pattern for each person, it is possible to learn the common pattern of aging for more than one person at different ages. For each age, more than one facial image is used for age representation. Each person can have several face images in one age or in an age range. Therefore, this model is more flexible than AGES model, and it is much easier to collect a larger number of samples (facial images) and create a larger database. This model uses a manifold embedding technique for learning a low-dimensional aging trend for many facial images of the same age. The only requirement of this model is that the sample size for learning is large enough so that embedded manifold can be taught with statistical sufficiency. The main objective of this book is to estimate age from different facial features. ¿ To detect face parts like eyes, nose, mouth, chin etc.¿ To extract facial features of the input face image.¿ To estimate age by using the extracted features of face.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch. N° de réf. du vendeur 9786202554121
Quantité disponible : 1 disponible(s)
Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Automatic Age Estimation from Face Images | Kailash Karande (u. a.) | Taschenbuch | 68 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202554121 | 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 118496545
Quantité disponible : 5 disponible(s)