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Recently, in the field of speech processing, I-Vector modeling has been appealed a great deal of interest. I-Vector has shown its benefits in modeling of intra and inter-domain variabilities to a single low dimension space for speaker identification tasks. This paper presents the usage of I-Vector in camera identification as a new approach in image forensics domain. In our approach, image texture...
Handwritten character recognition systems suffers from different training and testing sets distributions. In this paper, we propose a two-step domain adaptive multiple kernel learning algorithm, which learns a kernel function based on several kernels in the first step, and trains a target classifier by applying the learned kernel in the second step. Our method can be employed both in semi-supervised...
Automatic classification of modulation type in detected signals is an intermediate step between signal detection and demodulation, and is also an essential task for an intelligent receiver in various civil and military applications. In this paper, a new blind classification method is proposed for additive white Gaussian noise (AWGN) channels with unknown or variable signal to noise ratios. The algorithm...
In this paper, a new fast compressive sensing (CS) algorithm for phoneme classification is introduced. In this approach, unlike common CS classification approaches that use CS as a classifier, we use CS as an N-best class selector to limit the secondary classifier input into certain classes. In addition, we use a tree search strategy to select most similar training set for the specific test sample...
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