A Cognitive Ensemble of Extreme Learning Machines for Steganalysis Based on Risk-Sensitive Hinge Loss Function

@article{Sachnev2014ACE,
  title={A Cognitive Ensemble of Extreme Learning Machines for Steganalysis Based on Risk-Sensitive Hinge Loss Function},
  author={Vasiliy Sachnev and Savitha Ramasamy and Sundaram Suresh and Hyoung Joong Kim and Hee Joon Hwang},
  journal={Cognitive Computation},
  year={2014},
  volume={7},
  pages={103-110}
}
In this paper, we propose a risk-sensitive hinge loss function-based cognitive ensemble of extreme learning machine (ELM) classifiers for JPEG steganalysis. ELM is a single hidden-layer feed-forward network that chooses the input parameters randomly and estimates the output weights analytically. For steganalysis, we have extracted 548-dimensional merge… CONTINUE READING