2013, ISBN: 3659494577

[EAN: 9783659494574], Neubuch, [PU: LAP Lambert Academic Publishing Dez 2013], This item is printed on demand - Print on Demand Neuware - The dynamic synthesis of nonlinear feature functi… More...

[EAN: 9783659494574], Neubuch, [PU: LAP Lambert Academic Publishing Dez 2013], This item is printed on demand - Print on Demand Neuware - The dynamic synthesis of nonlinear feature functions is a challenging problem in object detection. This book presents a combinatorial approach of genetic programming and the expectation maximization algorithm (GP-EM) to synthesize nonlinear feature functions automatically for the purpose of object detection. The EM algorithm investigates the use of Gaussian mixture which is able to model the behaviour of the training samples during an optimal GP search strategy. Based on the Gaussian probability assumption, the GP-EM method is capable of performing simultaneously dynamic feature synthesis and model-based generalization. The EM part of the approach leads to the application of the maximum likelihood (ML) operation which provides protection against inter-cluster data separation and thus exhibits improved convergence. The experimental results show that the approach improves the detection accuracy and efficiency of pattern object discovery, as compared to some state-of-the-art methods for object detection existing in the literature. 64 pp. Englisch<

2013, ISBN: 3659494577

[EAN: 9783659494574], Neubuch, [PU: LAP Lambert Academic Publishing Dez 2013], Neuware - The dynamic synthesis of nonlinear feature functions is a challenging problem in object detection.… More...

[EAN: 9783659494574], Neubuch, [PU: LAP Lambert Academic Publishing Dez 2013], Neuware - The dynamic synthesis of nonlinear feature functions is a challenging problem in object detection. This book presents a combinatorial approach of genetic programming and the expectation maximization algorithm (GP-EM) to synthesize nonlinear feature functions automatically for the purpose of object detection. The EM algorithm investigates the use of Gaussian mixture which is able to model the behaviour of the training samples during an optimal GP search strategy. Based on the Gaussian probability assumption, the GP-EM method is capable of performing simultaneously dynamic feature synthesis and model-based generalization. The EM part of the approach leads to the application of the maximum likelihood (ML) operation which provides protection against inter-cluster data separation and thus exhibits improved convergence. The experimental results show that the approach improves the detection accuracy and efficiency of pattern object discovery, as compared to some state-of-the-art methods for object detection existing in the literature. 64 pp. Englisch<

ISBN: 9783659494574

The dynamic synthesis of nonlinear feature functions is a challenging problem in object detection. This book presents a combinatorial approach of genetic programming and the expectation m… More...

The dynamic synthesis of nonlinear feature functions is a challenging problem in object detection. This book presents a combinatorial approach of genetic programming and the expectation maximization algorithm (GP-EM) to synthesize nonlinear feature functions automatically for the purpose of object detection. The EM algorithm investigates the use of Gaussian mixture which is able to model the behaviour of the training samples during an optimal GP search strategy. Based on the Gaussian probability assumption, the GP-EM method is capable of performing simultaneously dynamic feature synthesis and model-based generalization. The EM part of the approach leads to the application of the maximum likelihood (ML) operation which provides protection against inter-cluster data separation and thus exhibits improved convergence. The experimental results show that the approach improves the detection accuracy and efficiency of pattern object discovery, as compared to some state-of-the-art methods for object detection existing in the literature. Bücher, Hörbücher & Kalender / Bücher / Sachbuch / Herstellung & Technik / Elektro- & Kommunikationstechnik<

2013, ISBN: 9783659494574

LAP LAMBERT Academic Publishing, Taschenbuch, 64 Seiten, Publiziert: 2013-12-12T00:00:01Z, Produktgruppe: Book, 0.23 kg, Ingenieurwissenschaft & Technik, Naturwissenschaften & Technik, Ka… More...

LAP LAMBERT Academic Publishing, Taschenbuch, 64 Seiten, Publiziert: 2013-12-12T00:00:01Z, Produktgruppe: Book, 0.23 kg, Ingenieurwissenschaft & Technik, Naturwissenschaften & Technik, Kategorien, Bücher, LAP LAMBERT Academic Publishing, 2013<

ISBN: 3659494577

Kartoniert / Broschiert, mit Schutzumschlag neu, [PU:LAP Lambert Academic Publishing]