A Survey of Face Recognition by the Genetic Algorithm

Fengzhi Dai, Yutaka Fujihara and Naoki Kushida
Tianjin University of Science and Technology, China, and others

Series: Computer Science, Technology and Applications
BISAC: COM014000

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Volume 10

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Volume 2

Volume 3

Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick

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Computer vision and recognition is playing an increasing important role in the modern intelligent control. Object detection is the first and the most important step in object recognition. Traditionally, special objects can be detected and recognized by the template matching method, but the recognition speed has always been a problem. Also for recognition by the neural network, training the data is always time consumption. In this book, the genetic algorithm-based face recognition system is examined. This book proposes a practical method for face detection and recognition. Finally, the experimental results, and a comparison with the traditional template matching method, and some other considerations, are also given. (Imprint: Nova)

ABSTRACT

INTRODUCTION

THEORY AND EXPERIMENTAL SETTING

EXPERIMENT AND COMPARISON

CONCLUSION

ACKNOWLEDGMENT

REFERENCES

INDEX

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