Yan, R., Fleury, M.-O., Merler, M., Natsev, A. and Smith, J.R. (2009) Large-Scale Multimedia Semantic Concept Modeling Using Robust Subspace Bagging and MapReduce. Proceedings of the 1st ACM Workshop on Large-Scale Multimedia Retrieval and Mining, Beijing, 23-23 October 2009, 35-42.

has been cited by the following article:

• TITLE: Hadoop and Its Role in Modern Image Processing

  AUTHORS: Seyyed Mojtaba Banaei, Hossein Kardan Moghaddam

  KEYWORDS: Cloud Computing, Hadoop, Big Data, Image Processing, MapReduce Model

  JOURNAL NAME: Open Journal of Marine Science, Vol.4 No.4, October 15, 2014

  ABSTRACT: This paper introduces MapReduce as a distributed data processing model using open source Hadoop framework for manipulating large volume of data. The huge volume of data in the modern world, particularly multimedia data, creates new requirements for processing and storage. As an open source distributed computational framework, Hadoop allows for processing large amounts of images on an infinite set of computing nodes by providing necessary infrastructures. This paper introduces this framework, current works and its advantages and disadvantages.