10.1145/3078897.3080536

This paper describes the applications of deep learning-based image recognition in the DARPA Memex program and its repository of 1.4 million weapons-related images collected from the Deep web. We develop a fast, efficient, and easily deployable framework for integrating Google's Tensorflow framework with Apache Tika for automatically performing image forensics on the Memex data. Our framework and its integration are evaluated qualitatively and quantitatively and our work suggests that automated, large-scale, and reliable image classification and forensics can be widely used and deployed in bulk analysis for answering domain-specific questions.

Suggested Citation: 

T. Gowda, K. Hundman, C. Mattmann. An Approach for Automatic and Large Scale Image Forensics and Search. Proceedings of the Multimedia Forensics and Security Workshop collocated with the ACM International Conference on Multimedia Retrieval (ICMR), Bucharest, Romania, June 2017. Pages 16-20. DOI: 10.1145/3078897.3080536

This material is based upon work supported by the National Science Foundation under Grant No. 1639675. Opinions, findings, conclusions or recommendations expressed are those of the authors and do not reflect the views of the NSF.