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Image forgery detection using steerable pyramid transform and local binary pattern
TLDR
A novel image forgery detection method is proposed based on the steerable pyramid transform (SPT) and local binary pattern (LBP). Expand
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An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning Approach
TLDR
We propose a system based on deep learning, which is an ensemble of pyramidal one-dimensional convolutional neural network (P-1D-CNN) models. Expand
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Passive copy move image forgery detection using undecimated dyadic wavelet transform
TLDR
A blind copy move image forgery detection method using undecimated dyadic wavelet transform (DyWT). Expand
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Passive detection of image forgery using DCT and local binary pattern
TLDR
A novel passive image forgery detection method is proposed based on local binary pattern (LBP) and discrete cosine transform (DCT) to detect copy–move and splicing forgeries. Expand
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Copy-Move Forgery Detection Using Dyadic Wavelet Transform
TLDR
In this paper, an efficient non-intrusive method for copy-move forgery detection is presented that outperforms the stat-of-the-art methods. Expand
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Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques
TLDR
This paper describes a discrete wavelet transform-based feature extraction scheme for the classification of EEG signals. Expand
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Evaluation of Image Forgery Detection Using Multi-Scale Weber Local Descriptors
TLDR
We employed two stat-of-the-art local texture descriptors:multi-scale Weber's law descriptor (multi-WLD) and multi-scale local binary pattern (Multi-LBP) for splicing and copy-move forgery detection. Expand
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Splicing image forgery detection based on DCT and Local Binary Pattern
TLDR
The authenticity of a digital image suffers from severe threats due to the rise of powerful digital image editing tools that easily alter the image contents without leaving any visible traces of such changes. Expand
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Comparison of Statistical, LBP, and Multi-Resolution Analysis Features for Breast Mass Classification
TLDR
This paper gives a comprehensive study of the effects of different features to be used in a CAD system for the classification of masses. Expand
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Optimized intrusion detection mechanism using soft computing techniques
TLDR
In this paper, we argue that feature selection is an important problem in intrusion detection and demonstrate that genetic algorithms (GAs) provide a simple, general, and powerful framework for selecting good subsets of features. Expand
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