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Learning to detect tables in document images using line and text information 学习使用行和文本信息检测文档图像中的表
International Conference on Machine Learning and Soft Computing Pub Date : 2018-02-02 DOI: 10.1145/3184066.3184091
Thong Huynh-Van, Khuong Nguyen-An, Trinh Le Ba Khanh, Hyung-Jeong Yang, T. A. Tran, Soohyung Kim
{"title":"Learning to detect tables in document images using line and text information","authors":"Thong Huynh-Van, Khuong Nguyen-An, Trinh Le Ba Khanh, Hyung-Jeong Yang, T. A. Tran, Soohyung Kim","doi":"10.1145/3184066.3184091","DOIUrl":"https://doi.org/10.1145/3184066.3184091","url":null,"abstract":"Table detection is a crucial step in many document analysis applications as tables are used for presenting essential information to readers in a structured manner. It is still a challenging problem due to the variety of table structures and the complexity of document layout. This paper presents a hybrid method consisting of three fundamental steps to detect table zones: classification of the regions, detection of the tables that constitute intersecting horizontal and vertical lines, and identification of the tables made up by only parallel lines. Experiments on the UW-III dataset show that the obtained results are very promising.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117138689","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
Collaborative filtering recommender system base on the interaction multi-criteria decision with ordered weighted averaging operator 基于有序加权平均算子的交互多准则决策协同过滤推荐系统
International Conference on Machine Learning and Soft Computing Pub Date : 2018-02-02 DOI: 10.1145/3184066.3184075
T. Huynh, H. Huynh, Vu The Tran, H. Huynh
{"title":"Collaborative filtering recommender system base on the interaction multi-criteria decision with ordered weighted averaging operator","authors":"T. Huynh, H. Huynh, Vu The Tran, H. Huynh","doi":"10.1145/3184066.3184075","DOIUrl":"https://doi.org/10.1145/3184066.3184075","url":null,"abstract":"In the recommender system, the most important is the decision-making solutionto consulte for user. Depending on the type and size of data stored, decision-making will always be improved to produce the best possible result.. The main task in implementing the model is to use methods to find the most valuable product or service for the user. In this paper, we propose a new approach to building a multi-user based collaborative filtering model using the interaction multi-criteria decision with ordered weighted averaging operator. This model demonstrates the synergy and interplay between user criteria for decision making. The model was evaluated through experimentation with the multirecsys tool on three datasets: MovieLense 100K, MSWeb and Jester5k. The experiment illustrated the model comparison with some other interactive multi-criteria counseling methods that have been researchedon both sparse datasets and thick datasets. In addition, the model is compared and evaluated with item-base collaborative filtering model using the interaction multi-criteria decision with ordered weighted averaging operator on two types of datasets. Consultancy results of the proposed model are quite effective compared to some traditional consulting models and some models with other operator. This counseling model can be applied well in a variety of contexts, especially in the case of sparse data, this model will give result in improved counseling. In addition, with the above method, the user-base model is always more efficient than item-base on all datasets.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"280 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124494591","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
Linear support vector machine to classify the vibrational modes for complex chemical systems 基于线性支持向量机的复杂化学系统振动模式分类
International Conference on Machine Learning and Soft Computing Pub Date : 2018-02-02 DOI: 10.1145/3184066.3184087
T. Le, T. Tran, Lam Huynh
{"title":"Linear support vector machine to classify the vibrational modes for complex chemical systems","authors":"T. Le, T. Tran, Lam Huynh","doi":"10.1145/3184066.3184087","DOIUrl":"https://doi.org/10.1145/3184066.3184087","url":null,"abstract":"Classification of vibrational modes into hindered internal rotation (HIR) and harmonic oscillation modes is important to obtain correct thermodynamic data for a chemical species for a wide range of temperatures. In this study, we propose a multivariate linear support vector machine (SVM) model to solve this challenging binary classification problem. The results of the proposed model were found to be similar to those of logistic regression and 2-5% better than those of the rule-based method. Moreover, the number of features found by linear SVM was also fewer than that of logistic regression (five versus six), which makes it easier to be interpreted by chemists. The detailed explanation of such differences is also presented. The three models were implemented in the GUI of the Multi-Species Multi-Channel Software Suite (Duong et al., Int. J. Chem. Kinet, 2015, 564) to facilitate the determination of HIR modes as well as the calculation of thermodynamic properties for a chemical species of interest.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124844004","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
On breast cancer detection: an application of machine learning algorithms on the wisconsin diagnostic dataset 乳腺癌检测:机器学习算法在威斯康星诊断数据集上的应用
International Conference on Machine Learning and Soft Computing Pub Date : 2017-11-20 DOI: 10.1145/3184066.3184080
Abien Fred Agarap
{"title":"On breast cancer detection: an application of machine learning algorithms on the wisconsin diagnostic dataset","authors":"Abien Fred Agarap","doi":"10.1145/3184066.3184080","DOIUrl":"https://doi.org/10.1145/3184066.3184080","url":null,"abstract":"This paper presents a comparison of six machine learning (ML) algorithms: GRU-SVM[1], Linear Regression, Multilayer Perceptron (MLP), Nearest Neighbor (NN) search, Softmax Regression, and Support Vector Machine (SVM) on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset[2] by measuring their classification test accuracy, and their sensitivity and specificity values. The said dataset consists of features which were computed from digitized images of FNA tests on a breast mass[2]. For the implementation of the ML algorithms, the dataset was partitioned in the following fashion: 70% for training phase, and 30% for the testing phase. The hyper-parameters used for all the classifiers were manually assigned. Results show that all the presented ML algorithms performed well (all exceeded 90% test accuracy) on the classification task. The MLP algorithm stands out among the implemented algorithms with a test accuracy of ≈99.04%.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"114 5-6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132193778","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: 186
Research on the De-Noising of Train Wheel-Rail Sound Signal 列车轮轨声信号的降噪研究
International Conference on Machine Learning and Soft Computing Pub Date : 1900-01-01 DOI: 10.1145/3036290.3036327
Qian Wang, Li-Juan Zhou, Q. Chen
{"title":"Research on the De-Noising of Train Wheel-Rail Sound Signal","authors":"Qian Wang, Li-Juan Zhou, Q. Chen","doi":"10.1145/3036290.3036327","DOIUrl":"https://doi.org/10.1145/3036290.3036327","url":null,"abstract":"Based on a new algorithm that combines spectral subtraction of multitaper estimation with signal self-correlation analysis, wheel-rail sound signal has been theoretically processed in this article. The simulation results show that the new algorithm results in better signal audio-visual and de-noising effects than the individual spectral subtraction of mulitaper without self-correlation one.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"6 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123542261","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
Evaluation of Vietnamese Speech Recognition Platforms 越南语语音识别平台的评价
International Conference on Machine Learning and Soft Computing Pub Date : 1900-01-01 DOI: 10.1145/3453800.3453826
H. T. Diep, Thi-My-Thanh Nguyen, Ngoc-Bich Le, Xuan-Quy Dao
{"title":"Evaluation of Vietnamese Speech Recognition Platforms","authors":"H. T. Diep, Thi-My-Thanh Nguyen, Ngoc-Bich Le, Xuan-Quy Dao","doi":"10.1145/3453800.3453826","DOIUrl":"https://doi.org/10.1145/3453800.3453826","url":null,"abstract":"∗The purpose of this paper is to evaluate the performance of Vietnamese speech recognition systems provided by top Vietnamese companies such as Vais, Vtcc, Fpt, and Google. This paper presents the results in applying Vietnamese automatic speech recognition systems in news, interview, and music domains. We use recorded audios as inputs to compare the performance of Vietnamese automatic speech recognition systems by calculating Word Error Rate. Vais and Viettel obtain good results in news and interview domains while Google has good results in the music domain. The results demonstrated that all the providers Vais, Viettel, Google, and Fpt achieve good results but Vais is more dominant.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128319594","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
Micro-expression recognition based on the fusion between optical flow and dynamic image 基于光流与动态图像融合的微表情识别
International Conference on Machine Learning and Soft Computing Pub Date : 1900-01-01 DOI: 10.1145/3453800.3453821
Nhi Thi Thu Nguyen, Duyen Thi Thu Nguyen, B. Pham
{"title":"Micro-expression recognition based on the fusion between optical flow and dynamic image","authors":"Nhi Thi Thu Nguyen, Duyen Thi Thu Nguyen, B. Pham","doi":"10.1145/3453800.3453821","DOIUrl":"https://doi.org/10.1145/3453800.3453821","url":null,"abstract":"Micro-expression (ME) is a subtle and involuntary facial expression that reveals the human's concealed emotion. Psychology studies pointed out that research of ME can build potential applications in many fields. Therefore, ME recognition (MER), one of the two main ME analysis tasks, has been becoming an attractive topic recently. However, the work of MER is still needed to consider due to several limitations related to performance and dataset. This paper proposes a feature fusion between optical flow and dynamic image to create a robust ME representation, which can be learned effectively from deep learning techniques. Experiments from two public datasets, CASME-II and SAMM, show that our method obtains higher performance than several existing studies and is very promising for future research. CCS CONCEPTS •Computing methodologies∼Object recognition","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126605162","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
Analysis of USBSCAN Driver USBSCAN驱动程序分析
International Conference on Machine Learning and Soft Computing Pub Date : 1900-01-01 DOI: 10.1145/3036290.3036329
Shengbao Wang, Jun Zhang, Qilong Tu
{"title":"Analysis of USBSCAN Driver","authors":"Shengbao Wang, Jun Zhang, Qilong Tu","doi":"10.1145/3036290.3036329","DOIUrl":"https://doi.org/10.1145/3036290.3036329","url":null,"abstract":"On the basis of the analysis of USBSCAN driver, it proposes the approaches to pack all the data needed in USBSCAN driving and to define by users themselves the relevant protocol. It also presents the process of opening the specified end point in USBSCAN driving. It offers definitions of some of the descriptors in USBSCAN data transmission.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121374235","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
Genetic Algorithm Based on Attribute Correlation for Multi-label Classification 基于属性关联的多标签分类遗传算法
International Conference on Machine Learning and Soft Computing Pub Date : 1900-01-01 DOI: 10.1145/3036290.3036317
Manli Hou, Zhihai Wang
{"title":"Genetic Algorithm Based on Attribute Correlation for Multi-label Classification","authors":"Manli Hou, Zhihai Wang","doi":"10.1145/3036290.3036317","DOIUrl":"https://doi.org/10.1145/3036290.3036317","url":null,"abstract":"The classifier chains (CC) model has been used widely for multi-label classification, its remarkable characteristic is in consideration of the association between the labels, and the CC method adds the classifiers before it to predict the current instance. Then, the association between the labels is added to each of the current classification of the instance. However, because the CC model requires all the labels to join the chain, the disadvantage of the CC model is that the labels with wrong or redundant information will affect the performance of the classifier. Considering the issue, this paper proposes a genetic algorithm (GA) based on attribute correlation for multi-label classification. The results of the experiments prove that the performance of classification can be improved.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115006756","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
Algebraic and Dynamic Analysis on the Modified Swarm Optimizers 改进群优化器的代数与动态分析
International Conference on Machine Learning and Soft Computing Pub Date : 1900-01-01 DOI: 10.1145/3036290.3036291
Weidong Jiao, Yonghua Jiang, Jizhong Shi, Xiaoyan Wang, Shixi Yang
{"title":"Algebraic and Dynamic Analysis on the Modified Swarm Optimizers","authors":"Weidong Jiao, Yonghua Jiang, Jizhong Shi, Xiaoyan Wang, Shixi Yang","doi":"10.1145/3036290.3036291","DOIUrl":"https://doi.org/10.1145/3036290.3036291","url":null,"abstract":"The modified particle swarm optimizers were proposed that use special velocity-updating modes and velocity-changing tracks to control velocity of evolved particles, and to tune the search process for the globally-optimal solution. Based on a reduced one-dimensional PSO system with only one particle, contrastive researches were made to interpret essential reasonability of the modified swarm optimizers, from both algebraic and dynamic viewpoint. Optimization example showed that the modified swarm optimizers are superior to the BPSO, on not only convergence precision but also computation expense.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123633809","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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