Gabor-Boosting Face Recognition - From Machine Learning Perspective
5 Angebote vergleichen
| Preise | 2013 | 2014 | 2015 | 2017 |
|---|---|---|---|---|
| Schnitt | € 61,39 | € 79,00 | € 79,00 | € 90,37 |
| Nachfrage |
1
Gabor-Boosting Face Recognition: From Machine Learning Perspective (2009)
EN PB NWISBN: 9783639214604 bzw. 3639214609, in Englisch, 256 Seiten, VDM Verlag Dr. Müller, Taschenbuch, neu.
جديد من: $77.11 (9 ويقدم)
تستخدم من: $235.88 (1 ويقدم)
إظهار المزيد 10 ويقدم في Amazon.com
Lieferung aus: Vereinigte Staaten von Amerika, Usually ships in 1-2 business days.
Von Händler/Antiquariat, marvelio.
In the past decade, face recognition has received much attention by both the commercial and public sectors in biometrics. This book describes a highly accurate appearance-based approach for face recognition - Gabor-Boosting.The strong performance of the Gabor-Boosting face recognition is highlighted by combining three key leading edge techniques - Gabor wavelet transform, AdaBoost, Support Vector Machine (SVM). The Gabor wavelet transform is used to extract features which describe texture variations of human faces. The AdaBoost algorithm is used to select most significant features which represent different individuals. The SVM constructs a classifier with high recognition accuracy. The Gabor-Boosting face recognition is extended into multi-class classification domain. The results show that the performance is improved by applying loosely controlled face recognition in the multi-class classification. The Gabor-Boosting face recognition is robust under conditions of small number of examples and selection-bias. It gives no false detections for impostors and high acceptance rate for clients in face verification. Paperback, التسمية: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, مجموعة المنتجات: Book, ونشرت: 2009-11-22, ستوديو: VDM Verlag Dr. Müller, رتبة المبيعات: 15841443.
Von Händler/Antiquariat, marvelio.
In the past decade, face recognition has received much attention by both the commercial and public sectors in biometrics. This book describes a highly accurate appearance-based approach for face recognition - Gabor-Boosting.The strong performance of the Gabor-Boosting face recognition is highlighted by combining three key leading edge techniques - Gabor wavelet transform, AdaBoost, Support Vector Machine (SVM). The Gabor wavelet transform is used to extract features which describe texture variations of human faces. The AdaBoost algorithm is used to select most significant features which represent different individuals. The SVM constructs a classifier with high recognition accuracy. The Gabor-Boosting face recognition is extended into multi-class classification domain. The results show that the performance is improved by applying loosely controlled face recognition in the multi-class classification. The Gabor-Boosting face recognition is robust under conditions of small number of examples and selection-bias. It gives no false detections for impostors and high acceptance rate for clients in face verification. Paperback, التسمية: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, مجموعة المنتجات: Book, ونشرت: 2009-11-22, ستوديو: VDM Verlag Dr. Müller, رتبة المبيعات: 15841443.
2
Gabor-Boosting Face Recognition: From Machine Learning Perspective (2009)
EN PB USISBN: 9783639214604 bzw. 3639214609, in Englisch, 256 Seiten, VDM Verlag Dr. Müller, Taschenbuch, gebraucht.
جديد من: $77.11 (9 ويقدم)
تستخدم من: $235.88 (1 ويقدم)
إظهار المزيد 10 ويقدم في Amazon.com
Lieferung aus: Vereinigte Staaten von Amerika, Usually ships in 1-2 business days.
Von Händler/Antiquariat, Red Rhino.
In the past decade, face recognition has received much attention by both the commercial and public sectors in biometrics. This book describes a highly accurate appearance-based approach for face recognition - Gabor-Boosting.The strong performance of the Gabor-Boosting face recognition is highlighted by combining three key leading edge techniques - Gabor wavelet transform, AdaBoost, Support Vector Machine (SVM). The Gabor wavelet transform is used to extract features which describe texture variations of human faces. The AdaBoost algorithm is used to select most significant features which represent different individuals. The SVM constructs a classifier with high recognition accuracy. The Gabor-Boosting face recognition is extended into multi-class classification domain. The results show that the performance is improved by applying loosely controlled face recognition in the multi-class classification. The Gabor-Boosting face recognition is robust under conditions of small number of examples and selection-bias. It gives no false detections for impostors and high acceptance rate for clients in face verification. Paperback, التسمية: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, مجموعة المنتجات: Book, ونشرت: 2009-11-22, ستوديو: VDM Verlag Dr. Müller, رتبة المبيعات: 15841443.
Von Händler/Antiquariat, Red Rhino.
In the past decade, face recognition has received much attention by both the commercial and public sectors in biometrics. This book describes a highly accurate appearance-based approach for face recognition - Gabor-Boosting.The strong performance of the Gabor-Boosting face recognition is highlighted by combining three key leading edge techniques - Gabor wavelet transform, AdaBoost, Support Vector Machine (SVM). The Gabor wavelet transform is used to extract features which describe texture variations of human faces. The AdaBoost algorithm is used to select most significant features which represent different individuals. The SVM constructs a classifier with high recognition accuracy. The Gabor-Boosting face recognition is extended into multi-class classification domain. The results show that the performance is improved by applying loosely controlled face recognition in the multi-class classification. The Gabor-Boosting face recognition is robust under conditions of small number of examples and selection-bias. It gives no false detections for impostors and high acceptance rate for clients in face verification. Paperback, التسمية: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, مجموعة المنتجات: Book, ونشرت: 2009-11-22, ستوديو: VDM Verlag Dr. Müller, رتبة المبيعات: 15841443.
3
Gabor-Boosting Face Recognition: From Machine Learning Perspective (2009)
EN PB NWISBN: 9783639214604 bzw. 3639214609, in Englisch, 256 Seiten, VDM Verlag Dr. Müller, Taschenbuch, neu.
جديد من: $77.11 (9 ويقدم)
تستخدم من: $235.88 (1 ويقدم)
إظهار المزيد 10 ويقدم في Amazon.com
Lieferung aus: Vereinigte Staaten von Amerika, Usually ships in 24 hours, بالإضافة إلى الشحن (في حالة شحنها).
Von Händler/Antiquariat, Amazon.com.
In the past decade, face recognition has received much attention by both the commercial and public sectors in biometrics. This book describes a highly accurate appearance-based approach for face recognition - Gabor-Boosting.The strong performance of the Gabor-Boosting face recognition is highlighted by combining three key leading edge techniques - Gabor wavelet transform, AdaBoost, Support Vector Machine (SVM). The Gabor wavelet transform is used to extract features which describe texture variations of human faces. The AdaBoost algorithm is used to select most significant features which represent different individuals. The SVM constructs a classifier with high recognition accuracy. The Gabor-Boosting face recognition is extended into multi-class classification domain. The results show that the performance is improved by applying loosely controlled face recognition in the multi-class classification. The Gabor-Boosting face recognition is robust under conditions of small number of examples and selection-bias. It gives no false detections for impostors and high acceptance rate for clients in face verification. Paperback, التسمية: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, مجموعة المنتجات: Book, ونشرت: 2009-11-22, ستوديو: VDM Verlag Dr. Müller, رتبة المبيعات: 15841443.
Von Händler/Antiquariat, Amazon.com.
In the past decade, face recognition has received much attention by both the commercial and public sectors in biometrics. This book describes a highly accurate appearance-based approach for face recognition - Gabor-Boosting.The strong performance of the Gabor-Boosting face recognition is highlighted by combining three key leading edge techniques - Gabor wavelet transform, AdaBoost, Support Vector Machine (SVM). The Gabor wavelet transform is used to extract features which describe texture variations of human faces. The AdaBoost algorithm is used to select most significant features which represent different individuals. The SVM constructs a classifier with high recognition accuracy. The Gabor-Boosting face recognition is extended into multi-class classification domain. The results show that the performance is improved by applying loosely controlled face recognition in the multi-class classification. The Gabor-Boosting face recognition is robust under conditions of small number of examples and selection-bias. It gives no false detections for impostors and high acceptance rate for clients in face verification. Paperback, التسمية: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller, مجموعة المنتجات: Book, ونشرت: 2009-11-22, ستوديو: VDM Verlag Dr. Müller, رتبة المبيعات: 15841443.
4
Gabor-Boosting Face Recognition
EN PB NWISBN: 9783639214604 bzw. 3639214609, in Englisch, VDM Verlag, Taschenbuch, neu.
In the past decade, face recognition has received much attention by both the commercial and public sectors in biometrics. This book describes a highly accurate appearance-based approach for face recognition - Gabor-Boosting.The strong performance of the Gabor-Boosting face recognition is highlighted by combining three key leading edge techniques - Gabor wavelet transform, AdaBoost, Support Vector Machine (SVM). The Gabor wavelet transform is used to extract features which describe texture variations of human faces. The AdaBoost algorithm is used to select most significant features which represent different individuals. The SVM constructs a classifier with high recognition accuracy. The Gabor-Boosting face recognition is extended into multi-class classification domain. The results show that the performance is improved by applying loosely controlled face recognition in the multi-class classification. The Gabor-Boosting face recognition is robust under conditions of small number of examples and selection-bias. It gives no false detections for impostors and high acceptance rate for clients in face verification.
Lade…