Special Issue on Concept Detection with Big Data


International Journal of Multimedia Information Retrieval


Guest editors

Shih-Fu Chang, Columbia University

Thomas S. Huang, University of Illinois at Urbana-Champaign

Michael S. Lew, Leiden University

Bart Thomee, Yahoo! Research


Important dates

Submission of manuscript: September 2nd (extensions possible - contact editors),  2014

Publication of special issue: Spring 2015



A grand challenge in information retrieval is concept detection in images, video, audio and text.  Contributions in this area are leading to bridging the semantic gap and allowing search engines to understand imagery at a deep level.  This special issue provides a focus on the state-of-the-art in concept detection with Big Data.  Big Data can be used for large scale concept detection (many images for many concepts) or in deep training of specific concepts (many images for a few concepts).



We recommend that the submissions address large well known datasets (a few examples would be ImageNet, MIRFLICKR, Wiki-Links, NUS-WIDE, ImageCLEF, YFCC100M or TRECVid.  Contributions using other large datasets are welcome)



Manuscripts must be submitted through the online submission system for IJMIR at   (then follow link: Submit Online)


Please select 'Special Issue: Concept Detection with Big Data' as the 'Article Type'. When submitting a manuscript which is an expanded version of a conference paper, the paper should be included as 'Supplementary Material' during submission. All manuscripts will be rigorously peer-reviewed.





If you have any questions, please feel free to email or contact the IJMIR EIC, Mike Lew at