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Research on Massive Image Classification Method Based on Parallel Hybrid Classifier Algorithm

Published: 06 August 2020 Publication History

Abstract

With the advent of the era of big data, various types of image data have exploded. Traditional image classification algorithms have the problems of low efficiency and low accuracy, and cannot meet the processing requirements of massive image data. Aiming at the above problems, this paper proposes a massive image classification method based on parallel hybrid classifier algorithm. This algorithm combines the Adaboost algorithm with the RBF algorithm, combines multiple RBF classifiers into a strong classifier, and uses the MapReduce parallel programming model to parallelize the Adaboost-RBF algorithm. The performance test of the algorithm was performed. using the Caltech256 data set. The test results show that compared with the ordinary Adaboost-RBF algorithm, the parallel hybrid classifier algorithm takes less time to run and the average classification accuracy is increased by 26%. This algorithm can meet the needs of automatic classification of massive images.

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  1. Research on Massive Image Classification Method Based on Parallel Hybrid Classifier Algorithm

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    HP3C 2020: Proceedings of the 2020 4th International Conference on High Performance Compilation, Computing and Communications
    June 2020
    191 pages
    ISBN:9781450376914
    DOI:10.1145/3407947
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University
    • City University of Hong Kong: City University of Hong Kong
    • Guangdong University of Technology: Guangdong University of Technology

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 06 August 2020

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    Author Tags

    1. Adaboost
    2. Image classification
    3. MapReduce
    4. Parallel hybrid classifier
    5. RBF neural network
    6. massive images

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