Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Machine Learning
Watermarking algorithm based on a human visual model
Signal Processing
Crowds: anonymity for Web transactions
ACM Transactions on Information and System Security (TISSEC)
Digital watermarking
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Information Hiding Techniques for Steganography and Digital Watermarking
Information Hiding Techniques for Steganography and Digital Watermarking
Some facets of complexity theory and cryptography: A five-lecture tutorial
ACM Computing Surveys (CSUR)
Digital Steganography: Hiding Data within Data
IEEE Internet Computing
Integration of digital rights management into the internet open trading protocol
Decision Support Systems
Proceedings of the First International Workshop on Information Hiding
Proceedings of the First International Workshop on Information Hiding
Attacks on Copyright Marking Systems
Proceedings of the Second International Workshop on Information Hiding
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Towards a perceptually optimal spectral amplitude estimator for audio signal enhancement
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
The use of digital watermarking for intelligence multimedia document distribution
Journal of Theoretical and Applied Electronic Commerce Research
Digital Watermarks for Audio Signals
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Intellectual Property Protection for Multimedia Information Technology
Intellectual Property Protection for Multimedia Information Technology
Digital Watermarking and Steganography
Digital Watermarking and Steganography
Two-step detection algorithm in a HVS-based blind watermarking of still images
IWDW'02 Proceedings of the 1st international conference on Digital watermarking
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In this paper, the authors propose information hiding by machine learning: a method of key generation for information extracting using neural network. The method consists of three layers for information hiding. First, the proposed method prepares feature extraction keys, which are saved by feature extraction attributes like feature coordinates and the region of frequency coefficients. Second, the proposed method prepares hidden patterns in advance to the embedding procedure as a watermark signal of the target contents. Finally, the proposed method generates information extraction keys by using machine learning to output presented hidden patterns. The proper hidden patterns are generated with the proper information extraction key and feature extraction key. In the experiments, the authors show that the proposed method is robust to high pass filtering and JPEG compression. The proposed method contributes to secure visual information hiding without damaging any detailed data of the target content.