2010 13th IEEE International Conference on Computational Science and Engineering最新文献_第7页

Medical Image Retrieval with Query-Dependent Feature Fusion Based on One-Class SVM 基于一类支持向量机的查询相关特征融合医学图像检索

2010 13th IEEE International Conference on Computational Science and Engineering Pub Date : 2010-12-11 DOI: 10.1109/CSE.2010.30

Y. Huang, Jun Zhang, Yongwang Zhao, Dian-fu Ma

{"title":"Medical Image Retrieval with Query-Dependent Feature Fusion Based on One-Class SVM","authors":"Y. Huang, Jun Zhang, Yongwang Zhao, Dian-fu Ma","doi":"10.1109/CSE.2010.30","DOIUrl":"https://doi.org/10.1109/CSE.2010.30","url":null,"abstract":"Due to the huge growth of the World Wide Web, medical images are now available in large numbers in online repositories, and there exists the need to retrieval the images through automatically extracting visual information of the medical images, which is commonly known as content-based image retrieval (CBIR). Since each feature extracted from images just characterizes certain aspect of image content, multiple features are necessarily employed to improve the retrieval performance. Meanwhile, experiments demonstrate that a special feature is not equally important for different image queries. Most of existed feature fusion methods for image retrieval only utilize query independent feature fusion or rely on explicit user weighting. In this paper, we present a novel query dependent feature fusion method for medical image retrieval based on one class support vector machine. Having considered that a special feature is not equally important for different image queries, the proposed query dependent feature fusion method can learn different feature fusion models for different image queries only based on multiply image samples provided by the user, and the learned feature fusion models can re¿ect the different importances of a special feature for different image queries. The experimental results on the IRMA medical image collection demonstrate that the proposed method can improve the retrieval performance effectively and can outperform existed feature fusion methods for image retrieval.","PeriodicalId":342688,"journal":{"name":"2010 13th IEEE International Conference on Computational Science and Engineering","volume":"332 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116051859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

A Novel Image Based CAPTCHA Using Jigsaw Puzzle 一种基于图像的拼图验证码

2010 13th IEEE International Conference on Computational Science and Engineering Pub Date : 2010-12-11 DOI: 10.1109/CSE.2010.53

Haichang Gao, Dan Yao, Honggang Liu, Xiyang Liu, Liming Wang

{"title":"A Novel Image Based CAPTCHA Using Jigsaw Puzzle","authors":"Haichang Gao, Dan Yao, Honggang Liu, Xiyang Liu, Liming Wang","doi":"10.1109/CSE.2010.53","DOIUrl":"https://doi.org/10.1109/CSE.2010.53","url":null,"abstract":"Most commonly used CAPTCHAs are text-based CAPTCHAs which relay on the distortion of texts in the background image. With the development of automated computer vision techniques, which have been designed to remove noise and segment the distorted strings to make characters readable for OCR, traditional text-based CAPTHCAs are not considered safe anymore for authentication. A novel image based CAPTCHA which involves in solving a jigsaw puzzle is presented in this paper. An image is divided into an n¡Án (n=3, 4 or 5, depends on security level) pieces to construct the jigsaw puzzle CAPTCHA. Only two of the pieces are misplaced from their original positions. Users are required to find the two pieces and swap them. Considering the previous works which are devoted to solving jigsaw puzzles using edge matching technique, the edges of all pieces are processed with glitch treatment to prevent the computer automatic solving. Experiments and security analysis proved that human users can complete the CAPTCHA verification quickly and accurately, but computers rarely can. It is a promising substitution to the current text-based CAPTCHA.","PeriodicalId":342688,"journal":{"name":"2010 13th IEEE International Conference on Computational Science and Engineering","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122532346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 56

Revealing Feasibility of FMM on ASIC: Efficient Implementation of N-Body Problem on FPGA 揭示FMM在ASIC上的可行性:n体问题在FPGA上的高效实现

2010 13th IEEE International Conference on Computational Science and Engineering Pub Date : 2010-12-11 DOI: 10.1109/CSE.2010.25

Zhe Zheng, Yongxin Zhu, Xu Wang, Zhiqiang Que, Tian Huang, X. Yin, Hui Wang, G. Rong, Meikang Qiu

引用次数: 6

Implementation of a Medical Image File Accessing System on Cloud Computing 基于云计算的医学图像文件访问系统的实现

2010 13th IEEE International Conference on Computational Science and Engineering Pub Date : 2010-12-11 DOI: 10.1109/CSE.2010.48

Chao-Tung Yang, Lung-Teng Chen, Wei-Li Chou, Kuan-Chieh Wang

{"title":"Implementation of a Medical Image File Accessing System on Cloud Computing","authors":"Chao-Tung Yang, Lung-Teng Chen, Wei-Li Chou, Kuan-Chieh Wang","doi":"10.1109/CSE.2010.48","DOIUrl":"https://doi.org/10.1109/CSE.2010.48","url":null,"abstract":"Large scale cluster based on cloud technologies has been widely used in many areas, including the data center and cloud computing environment. The purpose of presenting the research paper in this field was to solve the challenge in Medical Image exchanging, storing and sharing issues of EMR (Electronic Medical Record). In recent years, many countries invested significant resources on the projects of EMR topics. The benefit of the EMR included: Patient-centered Care, Collaborative Teams, Evidence-based Care, Redesigned Business Processes, Relevant Data Capture and Analysis and Timely Feedback and Education. For instance, the ARRAHIT project in Untied States (2011 - 2015), Health Infoway project in Canada (2001 - 2015) and NHIP project in Taiwan, etc. Aim to the topic of EMR, we presented a system called MIFAS (Medical Image File Accessing System) to solve the exchanging, storing and sharing on Medical Images of crossing the different hospitals issues. Through this system we can enhance efficiency of sharing information between patients and their caregivers. Furthermore, the system can make the bestpossible patient-care decisions.","PeriodicalId":342688,"journal":{"name":"2010 13th IEEE International Conference on Computational Science and Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115578375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 82

Enhancing LOCATION Information Using Semantic Composition 使用语义组合增强位置信息

2010 13th IEEE International Conference on Computational Science and Engineering Pub Date : 2010-12-01 DOI: 10.1109/CSE.2010.70

H. Cankaya, Eduardo Blanco, D. Moldovan

引用次数: 0