The main task of speech recognition is to enable computer to understand human languages (Lawrence, 1999; Jingwei et al., 2006). This makes it possible that machine can communicate with human. Usually, speech recognition includes three parts: pre-processing, feature extraction and training (recognition) network. In this paper, the speech recognition system is described as Fig. 1. It consists of ...

This paper introduces a new CBIR system based on two different approaches in order to achieve the retrieval efficiency and accuracy. Color and texture information is extracted and used in this work to form the feature vector. To do the texture feature extraction this system uses DCT and DCT Wavelet transform to generate the feature vectors of the query and database images. Color information ext...

This paper investigates the use of the Continuous Wavelet Transform (CWT) for detection of targets in cluttered environments. We rst deene the multiple 2D CWT energy densities in the feature space. We then use the spatial energy density as a computational core for our target-detection algorithm. Results from FLIR images are presented at the end of the paper. We used both the Mexican Hat wavelet...

Transformer differential protection may be of malfunction at the emergence of inrush current, and it will affect the normal operation of the transformer. So the paper puts forward a new application of wavelet energy spectrum entropy-neural network theory in transformer microcomputer protection, in which the multi-resolution analysis of wavelet transform and information entropy technology are co...

This paper describes a new technique for statistical 3{D object localization. Local feature vectors are extracted for all image positions, in contrast to seg-mentation in classical schemes. We deene a density function for those features and describe a hierarchical pose estimation scheme for the localization of a single object in a scene with arbitrary background. We show how the global pose sea...

in this paper, we review novel techniques in the emerging field of spatiotemporal 4d pet imaging. we will discuss existing limitations in conventional dynamic pet imaging which involves independent reconstruction of dynamic pet datasets. various approaches that seek to attempt some or all of these limitations are reviewed in this work, including techniques that utilize iterative temporal smooth...