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Digital information is packed into files when it is going to be stored on storage media. Each computer file is associated with a type. Type detection of computer data is a building block in different applications of computer forensics and security. Traditional methods were based on file extensions and metadata. The content-based method is a newer approach(More)
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Utilization of cyclostationarity is a fresh paradigm in texture classification. This paper employs the Strip Spectral Correlation Analyzer (SSCA) as the new and superior method of such a category. The SSCA has been much more computational efficient than the other spectral correlation estimators, such as the FFT-Accumulated Method (FAM) or Direct Frequency(More)
This paper introduces the wireless sensor networks (WSNs) as an ad-hoc network and their structure in general and provides a small survey on sensors (nodes) as an embedded mechanism. The survey mainly focuses on the main challenges of these networks, such as the network layers of WSNs, data transfer over WSNs, the approaches for routing and packet(More)
Motivated by the recent success of deep networks in providing effective and abstract image representations, in this paper, a multi-layer architecture called the multi-layer local energy patterns (ML-LEP) is proposed for texture representation and classification. The proposed approach follows a multi-layer convolutional neural network paradigm and is built(More)
– The purpose of this paper is to achieve a system with fast response. Necessary pre-processing to achieve the feature extraction stage are image segmentation, image normalization, image quality improvement and image denoising. After above steps we need to extract features and encode them .in this paper we used Symlet4 wavelet transform for extract(More)