2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)最新文献_第4页

Image emotional semantic annotation based on fusion features 基于融合特征的图像情感语义标注

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8301971

Xuliang Zhang, Sudi Lou

引用次数: 3

The application of improved threshold segmentation on detection of color fluff 改进阈值分割在颜色绒毛检测中的应用

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8302073

Hongze Xiao, Liqing Li, J. Wang, Shuhuai Huo

引用次数: 0

The application of compressed sensing reconstruction algorithms for MRI of glioblastoma 压缩感知重构算法在胶质母细胞瘤MRI中的应用

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8302072

Haowei Zhang, X. Ren, Y. Liu, Qi-Xu Zhou

引用次数: 1

Medical image retrieval based on the deep convolution network and hash coding 基于深度卷积网络和哈希编码的医学图像检索

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8302194

C. Qiu, Yiheng Cai, X. Gao, Yize Cui

引用次数: 8

Experimental study on single vector hydrophone positioning 单矢量水听器定位的实验研究

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8302125

Chuang Han, Xiaofeng Ma, Hongyue Qu, Zhongzheng Li

引用次数: 1

Raman spectroscopy analysis based on fourier transform for ABO blood group identification 基于傅立叶变换的拉曼光谱分析用于ABO血型鉴定

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8302232

Haihong Lin, Haotian Yu, Jichun Li, Encai Zhang, Guannan Chen

{"title":"Raman spectroscopy analysis based on fourier transform for ABO blood group identification","authors":"Haihong Lin, Haotian Yu, Jichun Li, Encai Zhang, Guannan Chen","doi":"10.1109/CISP-BMEI.2017.8302232","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2017.8302232","url":null,"abstract":"ABO blood type research is not only used for transfusion medicine, but also for the study of some diseases. In this study, principal component analysis is used to take the ABO blood group Raman spectrum of the Fourier transform, in order to improve the ABO blood typing sample recognition rate. When the principal component analysis is performed directly on the Raman spectrum, the differences between the ABO three blood samples can not be well recognized by the score data of the second and the twentieth main components. The Raman spectra of the fluorescence background is extracted from the Raman spectra by Fourier transform, so the imaginary part of the Raman spectrum is obtained. Then, the principal component of the imaginary part signal is analyzed, and fractional graphs of the second principal component and the twentieth principal component are used. In this way, the blood samples of type A, type B and O type are distinguished. The experimental results show that the principal component analysis is carried out by Fourier transform to improve the clustering effect of spectral data, making ABO three blood groups easier to be distinguished. The reason for the enhancement of the clustering effect is that the internal difference of the same kind of spectral data will be reduced and that the difference of the spectral data of different classes will be increased by Fourier transform.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"13 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86810516","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: 0

Moving target detection based on improved three frame difference and visual background extractor 基于改进三帧差分和视觉背景提取的运动目标检测

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8301906

Siyang Wu, Dongfang Chen, Xiaofeng Wang

引用次数: 5

A distance-based spectral clustering approach with L0 Gradient Minimization 基于L0梯度最小化的距离谱聚类方法

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8301974

Gang Shen, Yuteng Ye

{"title":"A distance-based spectral clustering approach with L0 Gradient Minimization","authors":"Gang Shen, Yuteng Ye","doi":"10.1109/CISP-BMEI.2017.8301974","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2017.8301974","url":null,"abstract":"Spectral clustering has recently achieved a plenty of successful applications in the fields of image processing and object pattern recognition. However, it is a frequent challenging problem that many spectral clustering algorithms suffer from the sensitivity in the selection of the parameters for their Gaussian kernel functions and K-means partitioning processes. To alleviate this situation, we first construct a distance matrix and project the data points into the eigen-space spanned by the selected eigenvectors, then we apply the proposed partitioning algorithm inspired by the continuity of data distribution. In order to partition the data points projected on the eigenvectors, we formulate a cost function with quadratic data-fidelity and L0 gradient constraint, and the optimal solution can be obtained with the use of alternating direction method of multipliers (ADMM). The proposed approach has been tested for the image segmentation problems. The experiments on the benchmark image datasets showed that the proposal was able to achieve efficient and effective results with the help of the superpixels.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"205 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87130039","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: 0

Research on event-related potentials in motor imagery BCI 运动想象脑机接口的事件相关电位研究

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8302267

Zhifeng Lin, Zhihua Huang

引用次数: 1

A modified joint-pixel based SAR interferogram auto-registration and denoising method 一种改进的联合像元SAR干涉图自动配准与去噪方法

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2017-10-01 DOI: 10.1109/CISP-BMEI.2017.8302027

Zhang Tao, L. Wan, Xiaolei Lv, Jun Hong

{"title":"A modified joint-pixel based SAR interferogram auto-registration and denoising method","authors":"Zhang Tao, L. Wan, Xiaolei Lv, Jun Hong","doi":"10.1109/CISP-BMEI.2017.8302027","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2017.8302027","url":null,"abstract":"A modified joint-pixel algorithm for autoregistration and interferometric phase denoising is proposed in this paper. For the blindness of the sample selection in joint-pixel method, this paper first analyzes the distribution that the sample obeyed. Under the guidance of this distribution, amplitude and phase estimation models of joint-pixel method are established. Through the preprocessing on the phase and amplitude of the two interferometric SAR images, an effective sample to estimate the true value is achieved. Moreover, taking advantage of the coherence information of the effective samples, the proposed method automatically registers the SAR images while denoising without the loss of detail. Compared with the original method, the interferogram can be estimated more accurate and the influence of the abnormal amplitude points on the surrounding is reduced. Furthermore, in order to solve the contradiction of preserving texture and filtering strength, an iterative algorithm is invented. In the end, the effectiveness of this modified algorithm is validated by both simulated and real data.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"27 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82684211","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: 0