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portada A Model Based Framework for Object Detection via Data Transformation
Type
Physical Book
Author
Publisher
Language
English
Pages
64
Format
Paperback
Dimensions
22.9x15.2x0.4 cm
Weight
0.10 kg.
ISBN13
9783659494574
Categories

A Model Based Framework for Object Detection via Data Transformation

Peifang Guo (Author) · Prabir Bhattacharya (Author) · LAP Lambert Academic Publishing · Paperback

A Model Based Framework for Object Detection via Data Transformation - Guo, Peifang ; Bhattacharya, Prabir

New Book Imported to Taiwan
Delivery: 23 Dec - 06 Jan Shipping: 13 to 14 business days.
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NT$ 1,536

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Synopsis "A Model Based Framework for Object Detection via Data Transformation"

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.

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