Deep CNN Combined With Relevance Feedback for Trademark Image Retrieval

Deep CNN Combined With Relevance Feedback for Trademark Image Retrieval

Trademark recognition and retrieval is a vital appliance component of content-based image retrieval (CBIR). Reduction in the semantic gap, attaining more accuracy, reduction in computation complexity, and hence in execution time, are the major challenges in designing and developing a trademark retri...

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Bibliographic Details
Main Authors: Pinjarkar Latika, Sharma Manisha, Selot Smita
Format: Article
Language:English
Published: De Gruyter 2018-09-01
Series:Journal of Intelligent Systems
Subjects:
content-based image retrieval (cbir)
deep convolutional neural networks (dcnns)
particle swarm optimization (pso)
self-organizing map (som)
relevance feedback
trademark
Online Access:https://doi.org/10.1515/jisys-2018-0083

Internet

https://doi.org/10.1515/jisys-2018-0083

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