Abstract
In this paper, a semantic image retrieval technique that efficiently depicts users’ perspective is proposed. It primarily aims in the representation of contextual diversity of the user through a high level semantic segmentation technique called DeepLab-V3+. An online user interactive step is also included during the retrieval process. The significance of intra-concept variation in image retrieval is clearly presented in this paper. An efficient database organization, which forms the essence of the retrieval methodology, based on concept co-occurrence and inter-concept distance is also proposed. ResNet-101 CNN features extracted from the regions are utilized in classification and retrieval tasks. The simulation results and performance analysis conducted on PASCAL VOC2012 and SUN ’09 datasets depict the superiority of the proposed technique over other approaches.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
