NDLI: Fast Co-operative Modular Neural Processors for Human Face Detection

Content Provider	IEEE Xplore Digital Library
Author	El-Bakry, H.M.
Copyright Year	2006
Description	Author affiliation: Mansoura Univ., El Mansoura (El-Bakry, H.M.)
Abstract	In this paper, a new approach to reduce the computation time taken by neural networks for the searching process is introduced. Both fast and cooperative modular neural networks are combined to enhance the performance of the detection process. Such approach is applied to identify human faces automatically in cluttered scenes. In the detection phase, neural networks are used to test whether a window of 20times20 pixels contains a face or not. The major difficulty in the learning process comes from the large database required for face/nonface images. A simple design for cooperative modular neural networks is presented to solve this problem by dividing these data into three groups. Such division results in reduction of computational complexity and thus decreasing the time and memory needed during the test of an image. Simulation results for the proposed algorithm on Bio database mixed with other images show a good performance.
Starting Page	1325
Ending Page	1332
File Size	489347
Page Count	8
File Format	PDF
ISBN	0780394909
DOI	10.1109/IJCNN.2006.246846
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-16
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Face detection Neural networks Testing Image databases Computer networks Layout Phase detection Computational complexity Computational modeling Cross Correlation in the Frequency Domain Fast Neural Networks Face Detection
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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