2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)最新文献_第3页

Segmentation of Pop Music Based on Histogram Clustering 基于直方图聚类的流行音乐分割

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633060

Rongshu Sun, Jingjing Zhang, Wei Jiang, Yuexin Hu

{"title":"Segmentation of Pop Music Based on Histogram Clustering","authors":"Rongshu Sun, Jingjing Zhang, Wei Jiang, Yuexin Hu","doi":"10.1109/CISP-BMEI.2018.8633060","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2018.8633060","url":null,"abstract":"As a method of music segmentation in music structure analysis, segmentation of music based on histogram clustering is to detect and discover musical repetition patterns on the basis of simulating human auditory perception. The selection of clustering algorithm is an important factor affecting the segmentation accuracy. In this paper, a music segmentation method based on histogram clustering is implemented. The beat-based pitch class profile (PCP)feature is selected, and the pop music is segmented according to the music structure through similar feature vector clustering, histogram clustering and marginal adjustment. The best parameters of histogram clustering were obtained by parameter optimization experiment. Using the traditional K-means, K-means++ and Isodata clustering algorithm, 200 Chinese pop songs were segmented and the performance of K-means++ algorithm was the best with an average accuracy of 71.34%. The results show that although the K-means++ algorithm has an increase in segmental redundancy, the average accuracy is greatly improved and the time complexity is lower, so it is more suitable for music segmentation based on histogram clustering.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"1010-1012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132050674","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: 3

Comparison of Five Numerical Simulation Algorithms in Temperature Prediction for Hollow Microspheres in Magnetic Induction Hyperthermia 五种数值模拟算法在空心微球磁感应热疗温度预测中的比较

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633156

Yandong Zhang, Xianwen Zhang, Liyan Zhang, Jintian Tang

{"title":"Comparison of Five Numerical Simulation Algorithms in Temperature Prediction for Hollow Microspheres in Magnetic Induction Hyperthermia","authors":"Yandong Zhang, Xianwen Zhang, Liyan Zhang, Jintian Tang","doi":"10.1109/CISP-BMEI.2018.8633156","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2018.8633156","url":null,"abstract":"Magnetic induction hyperthermia (MIH) uses high temperatures beyond 42°C to kill cancer cells. The temperature simulation is an essential part of the hyperthermia planning system. Pre-temperature simulations can help doctors decide the amount and the position of the magnetic agents. Most papers focus on only one numerical heat transfer algorithm to simulate temperature changes in MIH. They usually use software like FLUENT to calculate the temperature variation. Nevertheless, in practice, the core calculation code needs to be written by ourselves, combined with tumor model from CT images. We need to decide which heat transfer algorithm has the practical results. In this paper, we focus on the different forms of FDM. We use five heat transfer algorithms including the explicit format of FDM, Peaceman-Rachford ADI, Brian ADI, Douglas ADI and FVM to simulate. The results of simulations show that the approximations in FDM and FVM lead to relatively large offset compared with other simulations. In addition, the difference between the results of simulations and experiments is caused by the heat power used in simulations, the inaccuracy of physical parameters and measurement error.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"606 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132347955","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: 1

Fighting Detection Based on Pedestrian Pose Estimation 基于行人姿态估计的战斗检测

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633057

Huadong Pan, Jun Yin, Haohua Ku, Cheng Liu, Fubiao Feng, Jia Zheng, Shixian Luo

引用次数: 6

Identification and Classification of Electrocardiogram Signals Based on Convolutional Recurrent Neural Network 基于卷积递归神经网络的心电图信号识别与分类

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633273

Jinwei Ma, Shengping Liu, Guoming Chen

{"title":"Identification and Classification of Electrocardiogram Signals Based on Convolutional Recurrent Neural Network","authors":"Jinwei Ma, Shengping Liu, Guoming Chen","doi":"10.1109/CISP-BMEI.2018.8633273","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2018.8633273","url":null,"abstract":"Electrocardiogram (ECG)signals are important sign signal of human heart health. Arrhythmia is one of the main features of heart disease. Therefore, ECG signal recognition and classification have important clinical significance. In this paper, the ECG signals in the MIT - BIH standard library were used as sample data, which were identified and classified based on the algorithm of convolutional recurrent neural network (CRNN)in order to realize the intelligent identification and classification of ECG signals. The R-wave peak location and heartbeat segmentation of the ECG signals were performed on the sample data using the differential threshold method, and a convolutional recurrent neural network was constructed to identify and classify the signals. The classification results show that the overall recognition rate of ECG signals in the MIT - BIH database sample is 98.81 %, the recognition rate of normal ECG signals is up to 99.67%. The results show that the CRNN has strong generalization ability, fast convergence rate and a good recognition classification rate for ECG signals.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130270355","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: 2

A Novel Compression Algorithm for High-Throughput DNA Sequence Based on Huffman Coding Method 一种基于霍夫曼编码的高通量DNA序列压缩新算法

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633219

Chuan He, Huaiqiu Zhu

{"title":"A Novel Compression Algorithm for High-Throughput DNA Sequence Based on Huffman Coding Method","authors":"Chuan He, Huaiqiu Zhu","doi":"10.1109/CISP-BMEI.2018.8633219","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2018.8633219","url":null,"abstract":"NGS (Next generation sequencing) technology can concurrently accomplish sequencing of a large scale of DNA data in one time, resulting in a large number of DNA short reads. The transportation and processing of DNA data are thus faced with difficulties. There are two kinds of compression methods for high-throughput DNA data, reference-based method and reference-free method. Reference-free method is adaptive for compressing DNA data from different species without storing large genome for reference. In this paper, we proposed a reference-free algorithm, named HDC, realizing high-throughput DNA compression based on Huffman coding and dictionary method. The algorithm builds multiple dictionaries through Huffman coding and uses the dictionary to finish the compression and decompression. By testing on the genomes of human, green monkey and horse, HDC's lowest compression rate reaches 0.192 when compressing the human genome with chromosome as compression unit. We also compared HDC with a conventional compression algorithm gzip, and two reference-free DNA compression algorithms Leon and ORCOM. The result demonstrates that the HDC algorithm performs significantly best among the three algorithms.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134574275","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: 1

Robust Variational Optical Flow Algorithm Based on Rolling Guided Filtering 基于滚动引导滤波的鲁棒变分光流算法

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633237

Junjie Wu, Xuebing Wang, Zhen Chen, Congxuan Zhang

{"title":"Robust Variational Optical Flow Algorithm Based on Rolling Guided Filtering","authors":"Junjie Wu, Xuebing Wang, Zhen Chen, Congxuan Zhang","doi":"10.1109/CISP-BMEI.2018.8633237","DOIUrl":"https://doi.org/10.1109/CISP-BMEI.2018.8633237","url":null,"abstract":"In order to solve the excessive smoothness caused by existing optical flow algorithms within motion edge regions of images under difficult scenes, such as noise, illumination changes and shadows, occlusion, large displacement, and non-rigid motion, a robust variational optical flow estimation model based on the rolling guidance filter has been proposed in this paper. Firstly, the rolling guidance filter strategy is presented, and the energy function of the rolling guidance filter is designed. Secondly, a non-local total variation with L1 norm (TV-Ll) optical flow computational model based on the rolling guidance filter is constructed. Finally, the energy function is converted into a linear minimization of the TV-Ll optical flow through the multi-resolution pyramid refinement, and the flow field is computed at each layer. The rolling guidance filter is used to optimize the optical flow estimation alternately. The MPI-Sintel and KITTI test sequences are employed to evaluate the proposed algorithm and other state-of-the-art methods, including total variation regularization of local-global optical flow (CLG- TV), classic model with non-local constraint (Classic+ NL), and nearest neighbor fields (NNF). The experimental results showed that the proposed algorithm, compared with other contrast methods, has a better edge protection effect in difficult scenes and motion forms, which effectively improves the accuracy and robustness of the optical flow estimation.","PeriodicalId":117227,"journal":{"name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134354284","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: 2

Research of Barrage Analysis Based on Hypernetwork 基于超网络的弹幕分析研究

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633087

Shan Liu, Dingyi Lai, Xuanlong Zhu

引用次数: 0

Nodes Importance Research on the Airway Network of the Silk Road Economic Belt 丝绸之路经济带航线网络节点重要性研究

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633172

Yanbo Zhu, H. Fan

引用次数: 0

Automatic Classification of SAR Image Based on R-Gmm Algorithm 基于R-Gmm算法的SAR图像自动分类

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633230

Xiaodong Zhang, S. Ren

引用次数: 2

Reasearch on Pregnancy Hypertension Based on Data Mining 基于数据挖掘的妊娠高血压研究

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Pub Date : 2018-10-01 DOI: 10.1109/CISP-BMEI.2018.8633104

Xinke Lan, Wei Wu, Danhong Peng, Tian Xu, Jun Wang, Gongdao Wang, F. Hou

引用次数: 0