{"title":"基于纹理滤波器和塔克分解的ERP检测器","authors":"Rubén Álvarez-González, Andres Mendez-Vazquez","doi":"10.1109/ICCIA49625.2020.00049","DOIUrl":null,"url":null,"abstract":"Vision is the dominant sensory channel by which humans acquire external information. Understanding how the human brain responds to a visual stimulus will help us develop better brain-machine interfaces and describe the human-brain activity response. One technique for tracking brain activity is functional magnetic resonance imaging (fMRI) using blood-oxygen-level-dependent imaging or BOLD-contrast imaging to show the blood oxygenation in the brain before, during and after a stimulus. Identifying the brain activity provoked by a given stimulus is a topic in different research centers.When popular classifiers do not provide perfect accuracy in a practical application, possible causes of their failure can be deficiencies in the algorithms and intrinsic difficulties in the data. In machine and deep learning, models mostly remain black boxes; convolutional neural networks (CNN) are no exception. This understanding of the design of the machine-learning pipeline and the feature-extraction process will provide insight into what a classification model could be.","PeriodicalId":237536,"journal":{"name":"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"ERP Detector using Texture Filters and Tucker Decomposition\",\"authors\":\"Rubén Álvarez-González, Andres Mendez-Vazquez\",\"doi\":\"10.1109/ICCIA49625.2020.00049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vision is the dominant sensory channel by which humans acquire external information. Understanding how the human brain responds to a visual stimulus will help us develop better brain-machine interfaces and describe the human-brain activity response. One technique for tracking brain activity is functional magnetic resonance imaging (fMRI) using blood-oxygen-level-dependent imaging or BOLD-contrast imaging to show the blood oxygenation in the brain before, during and after a stimulus. Identifying the brain activity provoked by a given stimulus is a topic in different research centers.When popular classifiers do not provide perfect accuracy in a practical application, possible causes of their failure can be deficiencies in the algorithms and intrinsic difficulties in the data. In machine and deep learning, models mostly remain black boxes; convolutional neural networks (CNN) are no exception. This understanding of the design of the machine-learning pipeline and the feature-extraction process will provide insight into what a classification model could be.\",\"PeriodicalId\":237536,\"journal\":{\"name\":\"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIA49625.2020.00049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIA49625.2020.00049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ERP Detector using Texture Filters and Tucker Decomposition
Vision is the dominant sensory channel by which humans acquire external information. Understanding how the human brain responds to a visual stimulus will help us develop better brain-machine interfaces and describe the human-brain activity response. One technique for tracking brain activity is functional magnetic resonance imaging (fMRI) using blood-oxygen-level-dependent imaging or BOLD-contrast imaging to show the blood oxygenation in the brain before, during and after a stimulus. Identifying the brain activity provoked by a given stimulus is a topic in different research centers.When popular classifiers do not provide perfect accuracy in a practical application, possible causes of their failure can be deficiencies in the algorithms and intrinsic difficulties in the data. In machine and deep learning, models mostly remain black boxes; convolutional neural networks (CNN) are no exception. This understanding of the design of the machine-learning pipeline and the feature-extraction process will provide insight into what a classification model could be.