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2018 International Conference on Machine Learning and Cybernetics (ICMLC)最新文献

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ICMLC 2018 TOC
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/icmlc.2018.8526968
{"title":"ICMLC 2018 TOC","authors":"","doi":"10.1109/icmlc.2018.8526968","DOIUrl":"https://doi.org/10.1109/icmlc.2018.8526968","url":null,"abstract":"","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124466890","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 Face Image Clustering Based On Integrating Som And Spectral Clustering Algorithm 基于Som和光谱聚类算法的人脸图像聚类研究
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8526946
Lingfei Zhang, Chunfang Li, Hongru Wang, Min-Yong Shi
{"title":"Research On Face Image Clustering Based On Integrating Som And Spectral Clustering Algorithm","authors":"Lingfei Zhang, Chunfang Li, Hongru Wang, Min-Yong Shi","doi":"10.1109/ICMLC.2018.8526946","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8526946","url":null,"abstract":"With the rapid development of neural network and face recognition, the Convolution Neural Networks(CNN) is more and more widely applied. Considering the shortcomings of traditional clustering methods, spectral clustering and self-organizing feature mapping neural network (SOM), a variety of new clustering methods based on deep learning are constantly created. In this paper, firstly a convolutional neural network is used in automatically feature extraction. After extracting features with CNN, S-SOM, an integrated algorithm of SOM and spectral clustering, is proposed to cluster face image data. Finally, to verify the effectiveness of the method, an experiment is employed. Meanwhile, we also analyze the effect of some related parameters of S-SOM on face clustering for further research.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"379 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124725151","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: 6
Loan Default Prediction Using Diversified Sensitivity Undersampling 基于多元灵敏度欠采样的贷款违约预测
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8526936
Yanan Chen, Jianjun Zhang, Wing W. Y. Ng
{"title":"Loan Default Prediction Using Diversified Sensitivity Undersampling","authors":"Yanan Chen, Jianjun Zhang, Wing W. Y. Ng","doi":"10.1109/ICMLC.2018.8526936","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8526936","url":null,"abstract":"The loan default prediction is to predict rather the borrower will delay the repayment or not. This is an important problem for banking and finance companies. In this study, we focus on dealing with the data imbalance problem to enhance the performance of the loan default prediction. The approach in this study is a hybrid undersampling method that combines the clustering, the stochastic sensitivity measure and the radial basis function neural networks. A real loan default data from a P2P company in China is used to valid the performance of our method. Experiments results demonstrate that our approach yields a better generalization performance.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126138433","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: 17
Spectral-Spatial Sparse Subspace Clustering Based On Three-Dimensional Edge-Preserving Filtering For Hyperspectral Image 基于三维边缘保持滤波的高光谱图像光谱-空间稀疏子空间聚类
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527015
Ailin Li, Anyong Qin, Shuyan Hu, Zhaowei Shang, Yuanyan Tang
{"title":"Spectral-Spatial Sparse Subspace Clustering Based On Three-Dimensional Edge-Preserving Filtering For Hyperspectral Image","authors":"Ailin Li, Anyong Qin, Shuyan Hu, Zhaowei Shang, Yuanyan Tang","doi":"10.1109/ICMLC.2018.8527015","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527015","url":null,"abstract":"Due to the 3-D property of raw HSI cubes, 3-D spectral-spatial filter becomes an effective way for extracting spectral and spatial signatures from HSI. In this paper, a new spectral-spatial sparse subspace clustering framework based on 3-D edge-preserving filtering is proposed to improve the clustering accuracy of HSI. First, the initial sparse coefficient matrix is obtained in the s-parse representation process of the classical SSC model. Then, a 3-D edge-preserving filtering is conducted on the initial sparse coefficient matrix to get a more accurate one, which is used to build the similarity graph. Finally, the clustering result of H-SI data is achieved by employing the spectral clustering algorithm to the similarity graph. Specifically, the filtered matrix can not only capture the spectral-spatial features but the intensity differences. Experimental results demonstrate the potential of including the proposed 3-D edge-preserving filtering into the SSC framework can improve the clustering accuracy.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117306740","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: 10
Logical Disjunction Double-Quantitative Fuzzy Rough Sets 逻辑析取双定量模糊粗糙集
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527064
Yanting Guo, Eric C. C. Tsang, Weihua Xu, De-gang Chen
{"title":"Logical Disjunction Double-Quantitative Fuzzy Rough Sets","authors":"Yanting Guo, Eric C. C. Tsang, Weihua Xu, De-gang Chen","doi":"10.1109/ICMLC.2018.8527064","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527064","url":null,"abstract":"The variable precision rough set model mainly utilizes a controlled degree of misclassiffication between the concept and equivalence classes namely relative quantitative information to approximate a concept. And the graded rough set approximates a concept through internal and external inclusion degrees between the concept and equivalence classes namely absolute quantitative information. Both variable precision and graded rough sets can be used to handle databases with misclassiffication. However, these two models could not effectively handle the real-valued datasets because discretizing will lead to information loss. Therefore, we study the rough set theory by bidirectional quantization under fuzzy relations. Firstly, a logical disjunction double-quantitative fuzzy rough set model is proposed based on the bidirectional quantization. Secondly, we analyze relationships between approximations and different rough regions in the new model. Meanwhile, several important theorems are given to deepen understanding of related concepts. Finally, a medical data case is used to illustrate the importance of the study.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129948278","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: 4
Alarm System For Bed Exit And Prolonged Bed Rest 出床和长时间卧床的报警系统
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527027
Chien-Nan Lee, Su-Chen Yang, Chiu-Kuel Li, Min-Zheng Liu, Po-Chieh Kuo
{"title":"Alarm System For Bed Exit And Prolonged Bed Rest","authors":"Chien-Nan Lee, Su-Chen Yang, Chiu-Kuel Li, Min-Zheng Liu, Po-Chieh Kuo","doi":"10.1109/ICMLC.2018.8527027","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527027","url":null,"abstract":"In this study, we designed a system that senses bed pressure levels and provides alarms for bed exit and prolonged bed rest; the system uses pressure sensors, a single-chip microcontroller, and a computer. The designed system enables reducing bed exit falls due to muscle weakness among hospitalized patients, preventing pressure injury among patients restricted to prolonged bed rest, preventing wandering behavior among patients with dementia, and reducing the workload of nurses. Furthermore, the system can serve as an adequate substitute in situations in which 24-hours monitoring is impractical; additionally, it is a low-cost alternative to existing alarm systems. Therefore, this alarm system can be adopted as common medical-care equipment for hospitals and nursing homes.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123895248","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
Using Eeg Brainwaves And Deep Learning Method For Learning Status Classification 利用脑电波和深度学习方法进行学习状态分类
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527003
Chung-Yen Liao, R. Chen
{"title":"Using Eeg Brainwaves And Deep Learning Method For Learning Status Classification","authors":"Chung-Yen Liao, R. Chen","doi":"10.1109/ICMLC.2018.8527003","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527003","url":null,"abstract":"This study is conducted specifically to measure human's brain waves; the evaluation is built based on the energy of watching a video. Brainwave reflects the change in electrical potential resulting from the conjunction between the thousands of brain neurons. A neuron can receive signals from other neurons and starts off cyclic discharge reaction when sufficient energy is accumulated. That is also the reason why people persistently emit brainwaves. However, for some people rely on their brain to deal with many things and it may lead to learning status. The learning status includes good, questionable and bad. In this paper, we aim to classify their learning status by conducting choices in the system to be chosen when users watching to the video. Users need to click choices in the system. Then, using deep learning to predict their learning status through the experiments. The experimental results indicated this method is valuable for learning status predication.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127697043","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
Crack Detection Of Concrete Surface Based On Newline Convolutional Neural Networks 基于换行卷积神经网络的混凝土表面裂缝检测
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527035
G. Yao, Fujia Wei, Ji-Ye Qian, Zhaopan Wu
{"title":"Crack Detection Of Concrete Surface Based On Newline Convolutional Neural Networks","authors":"G. Yao, Fujia Wei, Ji-Ye Qian, Zhaopan Wu","doi":"10.1109/ICMLC.2018.8527035","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527035","url":null,"abstract":"Apparent quality of concrete is one of the important indexes of engineering quality assessment, occupying a very important position in the quality of engineering. As an important evaluation index of the apparent quality of concrete, the detection of cracks is particularly important. The traditional detection method mainly relies on the inspection personnel to carry out on-site inspection, which has low efficiency and large environmental limitations. In this paper, a method of crack image recognition based on convolution neural network is proposed, which can realize the automatic recognition of concrete surface cracks, and the recognition accuracy rate is as high as 93.7{%.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132351919","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: 4
Analysis of Endometrium Form by Using LBP for Female Infertility LBP法诊断女性不孕症子宫内膜形态分析
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527057
Kentaro Mori, K. Kitaya, T. Ishikawa, Y. Hata
{"title":"Analysis of Endometrium Form by Using LBP for Female Infertility","authors":"Kentaro Mori, K. Kitaya, T. Ishikawa, Y. Hata","doi":"10.1109/ICMLC.2018.8527057","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527057","url":null,"abstract":"In this study, we analyzed the feature of the uterine ultrasonic image in order to develop an image evaluative method to predict success of the pregnancy for female infertility patient. It is known that “Leaf pattern” is an indicator of success of pregnancy. A result using LBP found that a region of the endometrium composed by Edge. We confirmed that an angle of Edge was difference between “Homogeneous pattern and Pregnancy” and “Homogeneous pattern and No Pregnancy We evaluated a predictive rate of the pregnancy by using this angle. As an evaluation result, the overall accuracy was 69.7%, accuracy of Leaf pattern only was 60.0% and accuracy of Homogeneous pattern only 78.9%. We found that the high predictive rate was obtained for Homogeneous pattern by using this angle.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131800695","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
Apply Feature Expression Based On Food Energy And Als Algorithm To Recipe Concocting 基于食物能量的特征表达式和al算法在配方调制中的应用
2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8526964
Zhenfeng Lei, Defu Zhang, S. Aslam, Hua-Yi Yin
{"title":"Apply Feature Expression Based On Food Energy And Als Algorithm To Recipe Concocting","authors":"Zhenfeng Lei, Defu Zhang, S. Aslam, Hua-Yi Yin","doi":"10.1109/ICMLC.2018.8526964","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8526964","url":null,"abstract":"With the constant-depth research on the relationship between food and disease, relying on diet modification has been proved to make the disease condition improve or even cure. However, most of the research is currently based on how to better concoct recipes while ignoring the recipe expression. This paper first proposed two new recipe expression methods based on 2-tuple food-energy feature and 3-tuple food-energy-relationship feature using the energy value and the grey relational degree, which not only can solve the sparsity and binarization problems of the recipe matrix, but also can reflect the realistic energy re-lationship of different food in a recipe and the relationship of the same food in different recipes. Then, we used alternating least squares (ALS) for recipe concoction for the first time. Moreover, the non-smooth sparse matrix is introduced for better concocting recipes in the ALS-based model. Experiments on real-life data showed that the two recipe expression methods made 1.6% and 3.3% improvements respectively and the ALS algorithm can be applied well to the concoction of recipes.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133312719","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
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