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Dynamic weighted histogram equalization for contrast enhancement using for Cancer Progression Detection in medical imaging 利用动态加权直方图均衡增强对比度，用于医学成像中的癌症进展检测
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297086
Rashid Abbasi, Lixiang Xu, Z. Wang, Gohar Rehman Chughtai, Farhan Amin, B. Luo
{"title":"Dynamic weighted histogram equalization for contrast enhancement using for Cancer Progression Detection in medical imaging","authors":"Rashid Abbasi, Lixiang Xu, Z. Wang, Gohar Rehman Chughtai, Farhan Amin, B. Luo","doi":"10.1145/3297067.3297086","DOIUrl":"https://doi.org/10.1145/3297067.3297086","url":null,"abstract":"Contrast-enhancement is very essential and ideal to produce a maximum contrast of many computer-vision and image-processing applications with minimum brightness error. Moreover, there is no mechanism to control the brightness error, contrast in conventional histogram equalization and mean shift problem that is usually occurs when the histogram equalization based contrast enhancement methods has used. The purpose of this research is to devise an intelligently robust framework based on the image data that is collected during several phases of Ultrasound (US) cancer image by automating the real-time image enhancement, segmentation, classification and progression the widely spreading of cancer disease at initial stages moreover, we have proposed a new methodology of contrast optimization that overcomes the mean-shift problem. The data is collected and preprocessed, while image segmentation techniques has used to partition and extract the concerned object from the enhanced image.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129269670","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: 7
Machine Learning-Based Charging Network Operation Service Platform Reservation Charging Service System 基于机器学习的收费网络运营服务平台预约收费服务系统
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297078
Shu Su, Hui Yan, N. Ding
{"title":"Machine Learning-Based Charging Network Operation Service Platform Reservation Charging Service System","authors":"Shu Su, Hui Yan, N. Ding","doi":"10.1145/3297067.3297078","DOIUrl":"https://doi.org/10.1145/3297067.3297078","url":null,"abstract":"This paper proposes a machine learning-based electric vehicle (EV) reserved charging service system, which takes into consideration the impacts from both the power system and transportation system. The proposed framework of charging network operation service platform links the power system with transportation system through the charging navigation of massive EVs. The \"reserved charging + consumption\" integrated service model would be great significant for dealing with large-scale integration of electric vehicles. It applies the concept of charging time window to optimization of EV charging prediction for the reserved charging service system, and designs a dynamic dispatching model based on sliding time axis to make charging process of users get rid of constraints of queuing time and charging service fee period.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116798371","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
Improvement Research and Application of Text Recognition Algorithm Based on CRNN 基于CRNN的文本识别算法改进研究与应用
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297073
Lei Chen, Shaobin Li
{"title":"Improvement Research and Application of Text Recognition Algorithm Based on CRNN","authors":"Lei Chen, Shaobin Li","doi":"10.1145/3297067.3297073","DOIUrl":"https://doi.org/10.1145/3297067.3297073","url":null,"abstract":"This paper is based on CRNN model to recognize the text in the images of football matches scene, and two improvements are proposed. Considering the edge feature of text is strong, this paper adds MFM layers into CRNN model aiming to enhance the contrast. In order to solve the problem of losing details of image static features in the process of getting contextual features, this paper fuses up these two kinds of features. The training and testing experiments carried out on public dataset and manual dataset respectively verify the validity of the improvements, and the recognition accurate rate is higher than original model.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126008094","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: 5
Lip Reading using Simple Dynamic Features and a Novel ROI for Feature Extraction 基于简单动态特征的唇读和一种新的特征提取ROI
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297083
Abhilash Jain, G. Rathna
{"title":"Lip Reading using Simple Dynamic Features and a Novel ROI for Feature Extraction","authors":"Abhilash Jain, G. Rathna","doi":"10.1145/3297067.3297083","DOIUrl":"https://doi.org/10.1145/3297067.3297083","url":null,"abstract":"Deaf or hard-of-hearing people mostly rely on lip-reading to understand speech. They demonstrate the ability of humans to understand speech from visual cues only. Automatic lip reading systems work in a similar fashion - by obtaining speech or text from just the visual information, like a video of a person's face. In this paper, an automatic lip reading system for spoken digit recognition is presented. The system uses simple dynamic features by creating difference images between consecutive frames of the video input. Using this technique, word recognition rates of 83.79% and 65.58% are achieved in speaker-dependent and speaker-independent testing scenarios, respectively. A novel, extended region-of-interest (ROI) which includes lower jaw and neck region is also introduced. Most lip-reading algorithms use only the mouth/lip region for relevant feature extraction. Over simple mouth as the ROI, the proposed ROI improves the performance by 4% in speaker-dependent tests and by 11% in speaker-independent tests.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114174737","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
Location-based Fingerprint Downhole Mobile Node Localization Algorithm 基于位置的指纹井下移动节点定位算法
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297085
H. Zhu, Guanyu Wang, Liang Zhang
{"title":"Location-based Fingerprint Downhole Mobile Node Localization Algorithm","authors":"H. Zhu, Guanyu Wang, Liang Zhang","doi":"10.1145/3297067.3297085","DOIUrl":"https://doi.org/10.1145/3297067.3297085","url":null,"abstract":"Aiming at the problem that the wireless signal in coal mine is vulnerable to interference and the positioning accuracy of the node is low when moving, a positioning algorithm based on location fingerprint downhole mobile node is proposed. Firstly, based on the location fingerprint algorithm, the reference points with higher similarity are grouped, and KNN localization is performed respectively, and the position with large error is eliminated by the Grubbs criterion. Secondly, by generating a reasonable particle distribution and setting the particle collection method, the unscented particle filtering algorithm is improved, and the estimated position and state estimation are merged. The experimental results show that the algorithm of grouping KNN screening and improved unscented particle filtering algorithm improves the stability of the system and the positioning accuracy of the mobile node, and reduces the computational complexity of the algorithm.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132533909","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
Comprehensive Error Calibration Algorithm based on Non-uniform Dual Circular Array 基于非均匀双圆阵列的综合误差标定算法
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297090
Jiajia Zhang, Hui Chen, Meng-yu Ni, Jiangang Wang
{"title":"Comprehensive Error Calibration Algorithm based on Non-uniform Dual Circular Array","authors":"Jiajia Zhang, Hui Chen, Meng-yu Ni, Jiangang Wang","doi":"10.1145/3297067.3297090","DOIUrl":"https://doi.org/10.1145/3297067.3297090","url":null,"abstract":"In this paper, a comprehensive error calibration method is proposed for non-uniform dual circular arrays in the presence of gain-phase errors, position errors and mutual coupling errors. By rotating the platform, only one auxiliary calibration source is used to construct three time-sharing calibration sources. According to the orthogonality principle of signal subspace and noise subspace, the cost function is constructed, and the coefficients of gain-phase errors, position errors and mutual coupling errors are obtained through iteration. When the mutual coupling error is estimated, the algorithm makes full use of the structural characteristics of the non-uniform dual circular array. The algorithm does not require any additional auxiliary array element, the principle is simple and easy to implement. Simulation results show that the proposed algorithm can effectively calibrate the comprehensive error of non-uniform dual circular array.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125554556","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 the Signal De-noising Method of Acoustic Emission in Fused Silica Grinding 熔融石英磨削声发射信号去噪方法研究
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297071
Lian Zhou, Nan Zheng, Jian Wang, Qiancai Wei, Qinghua Zhang, Qiao Xu
{"title":"Research on the Signal De-noising Method of Acoustic Emission in Fused Silica Grinding","authors":"Lian Zhou, Nan Zheng, Jian Wang, Qiancai Wei, Qinghua Zhang, Qiao Xu","doi":"10.1145/3297067.3297071","DOIUrl":"https://doi.org/10.1145/3297067.3297071","url":null,"abstract":"The ultra-precision grinding process of brittle and hard fused silica is very complex. In order to monitor the grinding process accurately, it's necessary to de-noise the acoustic emission (AE) signals generated in this process and extract useful parameters which can characterize the cutting procedures of abrasive grain. Firstly, according to the characteristics of AE signal when single diamond grain scratching, the AE signal with white Gaussian noise during grinding process was simulated, whose SNR was below -2dB. Then the simulated AE signal was de-noised by wavelet threshold de-noising method, empirical mode decomposition (EMD) threshold de-noising method and EMD-Wavelet threshold de-noising method. Taking the signal to residual noise ratio (SRNR) and the mean square error (RMSE) as the evaluation parameters, the optimal way was EMD-Wavelet threshold de-noising method. The SRNR increased to 9dB, and the RMSE reduced to 0.017. At the end, the AE signal acquired from fused silica grinding process was de-noised by the optimal method, and the cutting process of the abrasive particles can be observed accurately. Taking the number and energy of impulse oscillation per unit time as key parameters, the accurate monitoring of the grinding process of fused silica material was realized.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126787059","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
Implementation of Irregular Meshes for the Sparse Representation of Multidimensional Signals 不规则网格在多维信号稀疏表示中的实现
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297082
S. Vishnyakov, Y. Vishnyakova, Elizaveta Sokolova
{"title":"Implementation of Irregular Meshes for the Sparse Representation of Multidimensional Signals","authors":"S. Vishnyakov, Y. Vishnyakova, Elizaveta Sokolova","doi":"10.1145/3297067.3297082","DOIUrl":"https://doi.org/10.1145/3297067.3297082","url":null,"abstract":"The paper is dedicated to development of effective tools of multidimensional digital signal processing on irregular meshes. ANN-based method of irregular mesh generation for intra-frame video coding is developed. The method described is based on artificial neural network implementation. Different architectures and types of artificial neural networks are compared. The training and testing sequences generation problem is discussed. The aim of the irregular mesh coverage of the two-dimensional signal (frame) is to decrease computational cost for the further motion detection between frames. The benefit of the artificial neural network usage is the relatively low computational cost of the mesh generation in comparison with analogous. The implementation of the irregular meshes for the correlation analysis between signals is discussed. Examples of the utilization of the irregular mesh-based FIR filtering for the open-boundary problem numerical solution are presented. Generalized results obtained may be used for pattern recognition, data compression, multidimensional look-up table interpolation.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133618526","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
A Comparative Analysis of Hyperopt as Against Other Approaches for Hyper-Parameter Optimization of XGBoost Hyperopt与其他XGBoost超参数优化方法的比较分析
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297080
Sayan Putatunda, K. Rama
{"title":"A Comparative Analysis of Hyperopt as Against Other Approaches for Hyper-Parameter Optimization of XGBoost","authors":"Sayan Putatunda, K. Rama","doi":"10.1145/3297067.3297080","DOIUrl":"https://doi.org/10.1145/3297067.3297080","url":null,"abstract":"The impact of Hyper-Parameter optimization on the performance of a machine learning algorithm has been proved both theoretically and empirically by many studies reported in the literature. It is a tedious and a time-consuming task if one goes for Manual Search. Some of the common approaches to address this include Grid search and Random search. Another alternative is performing the Bayesian optimization using the Hyperopt library in Python. In this paper, we tune the hyperparameters of XGBoost algorithm on six real world datasets using Hyperopt, Random search and Grid Search. We then compare the performances of each of these three techniques for hyperparameter optimization using both accuracy and time taken. We find that the Hyperopt performs better than the Grid search and Random search approaches taking into account both accuracy and time. We conclude that Bayesian optimization using Hyperopt is the most efficient technique for hyperparameter optimization.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122566364","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: 60
VMD Entropy Method and Its Application in Early Fault Diagnosis of Bearing VMD熵方法及其在轴承早期故障诊断中的应用
International Conference on Signal Processing and Machine Learning Pub Date : 2018-11-28 DOI: 10.1145/3297067.3297072
Hang Jin, Jianhui Lin, Xieqi Chen
{"title":"VMD Entropy Method and Its Application in Early Fault Diagnosis of Bearing","authors":"Hang Jin, Jianhui Lin, Xieqi Chen","doi":"10.1145/3297067.3297072","DOIUrl":"https://doi.org/10.1145/3297067.3297072","url":null,"abstract":"This paper proposes an early faults diagnosis method for bearings based on Variational Mode Decomposition (VMD) and Entropy Theory to monitor the working state of the key components of the high-speed train axle box. Firstly, the box vibration signal is decomposed into detailed signals at different scales by using VMD (Band-Limited Intrinsic Mode Function, BIMF), then the three kinds of entropy are extracted from BIMF and composed into VMD entropy. Finally, the VMD entropy has been input into SVM for training to determine the fault type. This paper is going to take research on the vibration signals of high-speed train axle box under three typical working conditions of normal bearing, cage failure and roller failure. It is concluded that the best VMD parameters of fault identification for high-speed train axle box can effectively improve the recognition rate of entropy in early bearing fault diagnosis by comparing it with EMD entropy. The analysis results show that for a high-speed train running under 200 km/h, the recognition rates under three different working conditions can reach 98.75%, 100%, 98.75% respectively, which proved the validity of VMD entropy for early bearing fault identification of high-speed train.","PeriodicalId":340004,"journal":{"name":"International Conference on Signal Processing and Machine Learning","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122121224","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
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