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In this paper, we propose an improved face recognition approach based on the combination of Vector Quantization (VQ) and Markov Stationary Feature (MSF) which obtain the extended MSF-VQ features from facial sub-regions for face recognition. It can not only utilize the MSF framework to extend the VQ histogram based features with the spatial structure information but can also incorporate more location...
Classification is the basis of electrocardiography (ECG) analysis. In the last decades, a large number of methods were proposed to deal with the classification of ECG beats. In this paper a kind of deep learning method is introduced into ECG beats classification. We create a classifier with stacked sparse autoencoder (SAE), and then combine the softmax regression with the SAE networks to consummate...
Face recognition is a typical application of biometrics identification technologies, which requires specific methods to obtain face representation as its features. In this paper, we apply a simple yet highly reliable method called Vector Quantization (VQ) to extract the features. Although VQ algorithm has been proven effective, the inability of VQ histogram features to convey spatial structure information,...
Aiming at the shorting of the existing atrial fibrillation (AF) detection algorithms and improve the ability of intelligent recognition and extraction of AF signals. Recently, deep learning theory with massive data has been used on image, voice and other filed widely. In this paper, a method based on the stack sparse autoencoder neural network, a instance of deep learning strategy, was proposed for...
With tandem mass spectrometry (MS/MS), spectra can be generated by various methods including collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), electron capture dissociation (ECD) and electron transfer dissociation (ETD). At the same time, de novo sequencing using multiple spectra from the same peptide is becoming popular in proteomics studies. The focus of this work...
In recent years, de novo peptide sequencing from mass spectrometry data has developed as one of the major peptide identification methods with the emergence of new instruments and advanced computational methods. However, there are still limitations to this method; for example, the typically used spectrum graph model cannot represent all the information and relationships inherent in tandem mass spectra...
In recent years, de novo peptide sequencing from mass spectrometry data has developed as one of the major peptide identification methods with the emergence of new instruments and advanced computational methods. However, there are still limitations to this method; for example, the typically used spectrum graph model cannot represent all the information and relationships inherent in tandem mass spectra...
Face recognition with occlusion is a challenging problem. Recently, the modular representation based method, i.e., modular linear regression based classification (MLRC) was proposed to deal with this problem. However, MLRC just simply combines the individual decision of each block within an image (based on the min rule) to make final decision. Therefore, the block distance information is not fully...
Field trip and on-site detection is widely regarded as an important part of the Earth and environmental sciences. However, the real field trips, due to the complexity of the real environment can not be implemented. This article aims to establish a teaching using virtual trips laboratory characteristics of the modelbased on virtual field trips to design appropriate teaching modules, and use java 3d...
This paper applied Multi-Agent to E-commerce personalized Recommender System, and designed E-commerce personalized Recommender System based on Multi-Agent, namely, MAPRS. Off-line recommendation and on-line hybrid recommendation are used to construct the core recommender model under the intelligent control. The paper presents the function and design ideas of various components of the system.
Five Viscera Tonifying Method (FVTM) was established by Prof. Gao Zhongying, a national prestigious and experienced practitioner of Traditional Chinese Medicine (TCM). This method extends the implication of tonfiying method while making a break-through in traditional TCM theories. With this featured method in pattern identification and herbal prescription, Prof. Gao is famed for his significant clinical...
It is well known that extracting effective features from images is a crucial step for appearance-based face recognition methods. In this paper, an effective framework for extracting discriminant features, by so called Discriminant Class-dependence Feature Analysis (DCFA), which combines Linear Discriminant Analysis (LDA) and 1-D Class-dependence Feature Analysis (1D-CFA), is proposed. From one side,...
To resolve the army's problems in training and teaching about the new equipment, a scheme of communication network simulation system was introduced after making a study of the internal constitution and command flow of the rocket battalion's communication network. UML and Rational Rose were applied to make the requirement analysis and overall design .With the help of the static views and activity views,...
Tool management is an important element in the efficiency of flexible manufacturing system. In order to supply fast and accurate results of tool preparation, a visualized cutting tool management methodology is presented. In the proposed methodology, a cutting tool management pattern and its detailed management process, including list management, tooling management, all tools management, standard tool...
Radio frequency identification (RFID) technology offers the possibility of significantly enhancing tool management and control process. A methodology of tool management and control based on RFID is proposed. In this proposed methodology, tool management and control process is mainly divided into two stages: tool preparation and tool usage. In the tool preparation stage, a centralized database which...
In this paper, a novel class-dependence feature analysis method based on Correlation Filter Bank (CFB) technique for effective multimodal biometrics fusion at the feature level is developed. In CFB, the unconstrained correlation filter trained for a specific modality is designed by optimizing the overall original correlation outputs. Therefore, the differences between modalities have been taken into...
Through massive experiments we found that for the binary text image embedding algorithm which hiding information by flipping central pixels of the image block, the statistics of run length between cover image and the image after been embedded is different obviously, but which between stego image and the image after test embedding is similar. Based on this law, a novel technique for the steganalysis...
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