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Artificial immune hybrid photo album classifier
Published in Springer Verlag
Volume: 459 AISC
Pages: 475 - 485
The personal photo collections are becoming significant in our day today existence. The challenge is to precisely intuit user’s complex and transient interests and to accordingly develop an adaptive and automated personalized photo management system which efficiently manages and organizes personal photos. This is increasingly gaining importance as it will be required to browse, search and retrieve efficiently the relevant information frompersonal collections whichmay extend from many years. Significance and relevance for the user also may undergo temporal and crucial shifts which need to be continually logged to generate patterns. The cloud paradigm makes available the basic platform but a system needs to be built wherein a personalized service with ability to capture diversity is guaranteed even when the training data size is small. An Artificial Immune Hybrid Photo Album Classifier (AIHPAC) is proposed using the nonlinear biological properties of Human Immune Systems. The system does event based clustering for an individual with embedded feature selection. The model is self learning and self evolving. The efficacy of the proposed method is efficiently demonstrated by the experimental results. © Springer Science+Business Media Singapore 2017.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Verlag