检索结果-内蒙古大学图书馆

3rd International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration, ICIICII 2017

作者： Pan, Zixiao Wang, Mei School of Automation Wuhan University of Technology Wuhan China Laboratory of Image Processing and Pattern Recognition Yantai Vocational College Yan China

ISBN: (纸本)9781538624340

For the image restoration problem of shredded paper broken by shredder with the same marginal feature, a new method based on spatial feature classification is proposed in this paper. Because no obvious marginal feature for rule shredder paper can be used to split, the feature similarity classification processing can greatly reduce the solution scale and improve the algorithm efficiency. The horizontal projection position of shredded paper image can be used to distinguish the same line for the shredded paper with words. Then the marginal moment invariants distance are defined by the left and right part spatial correlation information. The original order of adjacent shredded paper in the same line can be ensured by the minimum marginal distance. Similarly ordering up and down can be completed by the minimum marginal distance among up-down part stitching images. For the image stitching and restoration of large-scale rule shredded paper, the actual experimental result shows the good stability, efficiency and strong robustness. © 2017 IEEE.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

Fast KNN search for big data with set compression tree and best bin first 2

Fast KNN search for big data with set compression tree and b...

引用

2nd International Conference on Cloud Computing and Internet of Things, CCIOT 2016

作者： Chen, Zhenjie Yan, Jingqi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of Ministry of Education for System Control and Information Processing China Shanghai China

ISBN: (纸本)9781467398213

This paper proposes k nearest neighbors (kNN) search based on set compression tree (SCT) and best bin first (BBF) to deal with the problem for big data. The large compression rate by set compression tree is achieved by compressing the set of descriptors jointly instead of compressing on a per-descript or basis. So set compression tree has a good performance in kNN search at a low bit rate. At the same time, the best bin first (BBF) is a very efficient algorithm to find the approximately kNN from a large number of high dimensional feature descriptors. SCT-BBF is a novel exploration and it improves search performance in three aspects: First, SCT-BBF requires less memory footprint, which is important in big data age. Second, it increases accuracy compared traditional method like KD-Tree and original SCT. SCT-BBF can be used with other data processing methods like PCA and SIFT to perform better. Third, this paper adopts finer search to increase accuracy at a slight loss of speed. And it can extend to big data easily. © 2016 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

A general framework for machine vision: Hierarchical token grouping

A general framework for machine vision: Hierarchical token g...

引用

1994 International Symposium on Speech, image processing and Neural Networks, ISSIPNN 1994

作者： Huang, Qian Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East LansingMI48824 United States

ISBN: (纸本)078031865X

While the view of constructive and hierarchical vision prevails, the issues of cooperation and competition among individual modules become crucial. These issues are directly related to one of the most important aspects in computer vision research: integration. A major source of difficulty in developing a consistent and systematic integration formalism is the heterogeneity existing in modules, in information, and in knowledge. The author exploits, using the central theme of grouping, the homogeneous characteristics in vision problem solving and proposes a general framework, called hierarchical token grouping, that facilitates vision problem solving by providing a consistent and systematic environment for integrating modules, cues, and knowledge, all in a globally coherent mechanism. © 1994 IEEE.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Generalized quantum genetic algorithm of multidimensional space

Generalized quantum genetic algorithm of multidimensional sp...

引用

2014 International Conference on Logistics Engineering, Management and Computer Science, LEMCS 2014

作者： Zhang, Xiaofeng Miao, Wei Sui, Guifang Yang, Guowei Key Laboratory of JiangXi Procince for Image Processing and Pattern Recognition Information Engineering of NanChang HangKong University NanChang JiangXi330063 China

ISBN: (纸本)9789462520103

Quantum coding plays an important role in quantum genetic algorithm and affects the optimizing efficiency of algorithm, However, there are some defects in existing quantum genetic algorithm: the quantum coding scheme reduces the stability of the algorithm, making the algorithm easily occurs premature convergence and falls into local extremums. Therefore, coding scheme of multi gene chain is extended in a four dimensional space and multidimensional space based on an improved algorithm. Through simulation experiments of function extremum, combine double and triplestranded coding scheme, in accordance with the characteristics of qubits and the normalization condition. Through the experiment, study the effect of multiple genes encoding scheme chain on the performance of the algorithm. The results show that the optimal results of the algorithm can be better and the precision of solution can be higher by increasing the genetic chain. It is an effective strategy to improve the performance of algorithm. © 2014. The authors - Published by Atlantis Press.

关键词： Chains

来源：评论

学校读者我要写书评

暂无评论

Generative Adversarial Networks Based on MLP 14

Generative Adversarial Networks Based on MLP

引用

14th International Conference on Digital image processing, ICDIP 2022

作者： Ding, Hui Chen, Weifeng Li, Bo He, Zhifen School of Mathematics and Information Science Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China

ISBN: (纸本)9781510657564

Inspired by the state-of-the-art performance of MLP-Mixer on image classification task, multilayer perceptron (MLP) model attracts a number of researcher's attention again. Although various MLP architectures have been proposed, most of them focus on image classification domain. In this paper, we extend MLP to the task of image generation based on generative adversarial network (GAN). The pure MLP model is not friendly to small dataset because it is a data-hungry architecture. Thus, we leverage a hybrid model to solve the problem which uses MLP blocks as generator and CNN blocks as discriminator. Experimental results demonstrate that our model outperforms the pure CNN network on CIFAR-10 dataset in view of two different evaluation metrics. Besides, we apply eight widely popular MLP structures to our generator to validate which one achieves the most excellent performance in image generation task. © 2022 SPIE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Recognizing elongated objects using invariant surface features and matched filters 2

Recognizing elongated objects using invariant surface featur...

引用

Mathematical Methods in Medical Imaging II 1993

作者： Huang, Qian Stockman, George C. Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East LansingMI48824 United States

Many biological objects are elongated. This research addresses the issue of recognizing elongated objects from both 2D intensity images and 3D volumes. A mathematical model, called tube model, is developed for this class of objects and is effectively utilized in two stages of recognition. The explicit relationships between geometrical surface features and the object model parameters are quantitatively exploited to automatically locate seeds for recognition. Invariant surface features are used to constrain or hypothesize the objects of interest. The verification of a hypothesis is performed by correlating a matched filter, dynamically generated based on the hypothesis, with the sensor data. The tubes identified in such a local recognition process serve as the seeds from which the global recognition process is initiated. Each seed is swept along the trajectory where the best-fit is found. A smooth sweep is controlled by a set of adaptive constraints computed dynamically from an on-line sweeping history. We apply the proposed method to real world data from different application domains. Experimental results are presented and discussed. © 1993 SPIE. All rights reserved.

关键词： Matched filters

来源：评论

学校读者我要写书评

暂无评论

Improved global optical flow estimation with mean shift algorithm for target detection

引用

International Journal of Wireless and Mobile Computing 2015年第4期8卷 323-328页

作者： Wang, Zhonghua Li, Chunyong Liu, Qingping Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang Jiangxi Province330063 China School of Information and Engineering Nanchang Hangkong University Nanchang Jiangxi Province330063 China

In view of the problem that the global optical flow algorithm cannot acquire accurate motion parameter estimation at a low-gradient value, an improved method has been presented in order to enhance the self-adaptive ability. The proposed method is divided into three steps: firstly, the Gaussian filter is used to restrain the background noise;secondly, the optical basic constraint weighted function is modified to acquire targets area;finally, the morphological filtering and mean shift segmentation algorithm is adopted to reduce the false alarm rate. Compared with other algorithms, the experiment results show that the proposed method can improve the self-adaptive ability and the detection rate. © 2015 Inderscience Enterprises Ltd.

关键词： Optical flows

来源：评论

学校读者我要写书评

暂无评论

A Novel Wideband CPW-Fed 5.8GHz RFID Tag Antenna

引用

电子学报(英文版) 2012年第2期21卷 202-208页

作者： LI Huihui MOU Xuanqin JI Zhen YU Hang LI Yan Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an 710049 China College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China Shenzhen Key Laboratory of Embedded System Design Shenzhen 518060 China

A novel wideband 5.8GHz CPW-fed an- tenna is presented for Radio frequency identification (RFID) tag. Four U-shaped and four L-shaped branches are used as additional resonators to achieve wideband operation. The proposed antenna was analyzed numeri- cally using the Method of moment (MOM) and the Fi- nite element method (FEM). With the antenna size lim- ited to 30 × 30mm2, the ?10dB bandwidth obtained by MOM is 3.235GHz (5.765～9GHz) and the ?9.5dB band- width obtained by FEM is 2.74GHz (5.32～8.06GHz), cor- responding to 55.7% and 47.2% of the center frequency 5.8GHz respectively. Moreover, the simulated results show that the proposed antenna has gain of more than 4.8dBi and the radiation pattern is nearly omnidirectional in the H-plane. The measured ?10dB bandwidth is 2.68GHz (5.63GHz～8.31GHz), 46.2% of the 5.8GHz frequency. Fur- thermore, there are three measured resonant frequencies at 1.34GHz, 3.23GHz and 5.8GHz with lower than ?10dB return loss respectively. The measurement result achieves a wideband RFID tag antenna performance and is in good agreement with the calculated results.

关键词： RFID标签天线尺寸共面波导宽带无线电频率识别有限元分析网络连接数值分析

来源：评论

学校读者我要写书评

暂无评论

Machine learning techniques and chi-square feature selection for cancer classification using SAGE gene expression profiles

引用

PAKDD 2006 Workshop on Data Mining for Biomedical Applications, BioDM 2006

作者： Jin, Xin Xu, Anbang Bie, Rongrang Guo, Ping College of Information Science and Technology Beijing Normal University Beijing 100815 China Image Processing and Pattern Recognition Laboratory Beijing Normal University

ISBN: (纸本)3540331042

Recently developed Serial Analysis of Gene Expression (SAGE) technology enables us to simultaneously quantify the expression levels of tens of thousands of genes in a population of cells. SAGE is better than Microarray in that SAGE can monitor both known and unknown genes while Microarray can only measure known genes. SAGE gene expression profiling based cancer classification is a better choice since cancers may be due to some unknown genes. Whereas a wide range of methods has been applied to traditional Microarray based cancer classification, relatively few studies have been done on SAGE based cancer classification. In our study we evaluate popular machine learning methods (SVM, Naive Bayes, Nearest Neighbor, C4.5 and RIPPER) for classifying cancers based on SAGE data. In order to deal with the high dimensional problem, we propose to use Chi-square for tag/gene selection. Both binary classification and multicategory classification are investigated. The experiments are based on two human SAGE datasets: brain and breast. The results show that SVM and Naive Bayes are the top-performing SAGE classifiers and that Chi-square based gene selection can improve the performance of all the five classifiers investigated. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Biotechnology

来源：评论

学校读者我要写书评

暂无评论

Formal Photograph Compression Algorithm Based on Object Segmentation

引用

International Journal of Automation and computing 2008年第3期5卷 276-283页

作者： Li Zhu Guo-You Wang Chen Wang Laboratory. for Biomedical Image Processing Institute for Pattern Recognition ＆ Artificial Intelligence Huazhong University of Science ＆ Technology Wuhan 430074 PRC School of Mechanical and Aeropace Engineering Nanyang Technological Vnlversity Sigapore 639798 Sigapore

Small storage space for photographs in formal documents is increasingly necessary in today＇s needs for huge amounts of data communication and storage. Traditional compression algorithms do not sufficiently utilize the distinctness of formal photographs. That is, the object is an image of the human head, and the background is in unicolor. Therefore, the compression is of low efficiency and the image after compression is still space-consuming. This paper presents an image compression algorithm based on object segmentation for practical high-efficiency applications. To achieve high coding efficiency, shape-adaptive discrete wavelet transforms are used to transformation arbitrarily shaped objects. The areas of the human head and its background are compressed separately to reduce the coding redundancy of the background. Two methods, lossless image contour coding based on differential chain, and modified set partitioning in hierarchical trees （SPIHT） algorithm of arbitrary shape, are discussed in detail. The results of experiments show that when bit per pixel （bpp）is equal to 0.078, peak signal-to-noise ratio （PSNR） of reconstructed photograph will exceed the standard of SPIHT by nearly 4dB.

关键词： image compression object segmentation lossless image contour coding differential chain set partitioning in hierarchical trees (SPIHT) coding of arbitrarily shaped object.

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：