Genetic programming evolved spatial descriptor for Indian monuments classification

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Bhatt:2015:ieeeCGVIS,

• author = "M. S. Bhatt and T. P. Patalia",
• booktitle = "2015 IEEE International Conference on Computer Graphics, Vision and Information Security (CGVIS)",
• title = "Genetic programming evolved spatial descriptor for Indian monuments classification",
• year = "2015",
• pages = "131--136",
• abstract = "Travel and tourism are the largest service industries in India. Every year people visit tourist places. and upload pictures of their visit on social networking sites or share via mobile device with friends and relatives. Millions of such photographs are uploaded and it is almost impossible to manually classify these pictures as per the monuments they have visited. Classification is helpful to hoteliers for development of new hotel with state of the art amenities, to travel service providers, to restaurant owners, to government agencies for security etc. The proposed system extracts Genetic programming evolved spatial descriptor and classifies the Indian monuments visited by tourists based on linear Support Vector Machine(SVM). The proposed system is divided into 3 main phases: preprocessing, genetic programming evolution and classification. The Preprocessing phase converts images into a form suitable for processing by genetic programming system using Generalized Co-Occurrence Matrix. The second phase generates best so far spatial descriptor in the form of program based on the fitness. The Fitness is calculated using SVM. Once program is obtained as output it can be used for classification. The proposed system is implemented in MATLAB and achieves high accuracy.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/CGVIS.2015.7449908",
• month = nov,
• notes = "Also known as \cite{7449908}",

}

Genetic Programming entries for M S Bhatt T P Patalia

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