Coarse-Grain Parallelization of Neural Network-Based Face Detection Method

Volodymyr Turchenko; Ihor Paliy; Viktor Demchuk; Ruslan Smal; Lev Legostaev

doi:10.1109/idaacs.2007.4488395

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Coarse-Grain Parallelization of Neural Network-Based Face Detection Method

Volodymyr Turchenko Ihor Paliy Viktor Demchuk Ruslan Smal Lev Legostaev

Year: 2007

DOI: 10.1109/idaacs.2007.4488395

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Abstract

The paper describes the coarse-graining paralleling of the neural networks' cascade training for the face detection method. The training parallelizing is done on Grid system using MPI technology. Experimental results show the decreasing of training time for the neural networks' cascade in 1.3 times compared with a sequential execution on a single uniprocessor machine.

Keywords:

Computer science Uniprocessor system Granularity Artificial neural network Cascade Face (sociological concept) Face detection Parallel computing Artificial intelligence Pattern recognition (psychology) Facial recognition system Operating system

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Distributed and Parallel Computing Systems

Physical Sciences → Computer Science → Computer Networks and Communications

Advanced Data Processing Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Geological Modeling and Analysis

Physical Sciences → Earth and Planetary Sciences → Geochemistry and Petrology

Coarse-Grain Parallelization of Neural Network-Based Face Detection Method

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