{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T05:00:55Z","timestamp":1726030855575},"publisher-location":"Cham","reference-count":11,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030205201"},{"type":"electronic","value":"9783030205218"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-20521-8_72","type":"book-chapter","created":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T23:02:40Z","timestamp":1559689360000},"page":"883-894","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Convolutional Neural Networks and Feature Selection for BCI with Multiresolution Analysis"],"prefix":"10.1007","author":[{"given":"Javier","family":"Le\u00f3n","sequence":"first","affiliation":[]},{"given":"Julio","family":"Ortega","sequence":"additional","affiliation":[]},{"given":"Andr\u00e9s","family":"Ortiz","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,16]]},"reference":[{"key":"72_CR1","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1109\/34.75512","volume":"3","author":"SJ Raudys","year":"1991","unstructured":"Raudys, S.J., Jain, A.K.: Small sample size effects in statistical pattern recognition: recommendations for practitioners. IEEE Trans. Pattern Anal. Mach. Intell. 3, 252\u2013264 (1991)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"72_CR2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611970104","volume-title":"Ten Lectures on Wavelets","author":"I Daubechies","year":"1992","unstructured":"Daubechies, I.: Ten Lectures on Wavelets, vol. 61. Siam, Philadelphia (1992)"},{"issue":"4","key":"72_CR3","doi-asserted-by":"publisher","first-page":"046014","DOI":"10.1088\/1741-2560\/10\/4\/046014","volume":"10","author":"J Asensio-Cubero","year":"2013","unstructured":"Asensio-Cubero, J., Gan, J., Palaniappan, R.: Multiresolution analysis over simple graphs for brain computer interfaces. J. Neural Eng. 10(4), 046014 (2013)","journal-title":"J. Neural Eng."},{"issue":"3","key":"72_CR4","doi-asserted-by":"publisher","first-page":"031005","DOI":"10.1088\/1741-2552\/aab2f2","volume":"15","author":"F Lotte","year":"2018","unstructured":"Lotte, F., et al.: A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update. J. Neural Eng. 15(3), 031005 (2018)","journal-title":"J. Neural Eng."},{"issue":"1","key":"72_CR5","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen, J.: A coefficient of agreement for nominal scales. Educ. Psychol. Measur. 20(1), 37\u201346 (1960)","journal-title":"Educ. Psychol. Measur."},{"issue":"1","key":"72_CR6","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1186\/1743-0003-10-106","volume":"10","author":"W Yi","year":"2013","unstructured":"Yi, W., Qiu, S., Qi, H., Zhang, L., Wan, B., Ming, D.: EEG feature comparison and classification of simple and compound limb motor imagery. J. Neuroengineering Rehabilitation 10(1), 106 (2013)","journal-title":"J. Neuroengineering Rehabilitation"},{"issue":"2","key":"72_CR7","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.jneumeth.2010.09.010","volume":"193","author":"J Li","year":"2010","unstructured":"Li, J., Zhang, L.: Bilateral adaptation and neurofeedback for brain computer interface system. J. Neurosci. Methods 193(2), 373\u2013379 (2010)","journal-title":"J. Neurosci. Methods"},{"issue":"3","key":"72_CR8","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"key":"72_CR9","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization, arXiv preprint \n                      arXiv:1412.6980\n                      \n                     (2014)"},{"key":"72_CR10","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra, J., Bengio, Y.: Random search for hyper-parameter optimization. J. Mach. Learn. Res. 13, 281\u2013305 (2012)","journal-title":"J. Mach. Learn. Res."},{"key":"72_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/978-3-319-59153-7_3","volume-title":"Advances in Computational Intelligence","author":"J Ortega","year":"2017","unstructured":"Ortega, J., Ortiz, A., Mart\u00edn-Smith, P., Gan, J.Q., Gonz\u00e1lez-Pe\u00f1alver, J.: Deep belief networks and multiobjective feature selection for BCI with multiresolution analysis. In: Rojas, I., Joya, G., Catala, A. (eds.) IWANN 2017. LNCS, vol. 10305, pp. 28\u201339. Springer, Cham (2017). \n                      https:\/\/doi.org\/10.1007\/978-3-319-59153-7_3"}],"container-title":["Lecture Notes in Computer Science","Advances in Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20521-8_72","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T23:10:09Z","timestamp":1559689809000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20521-8_72"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030205201","9783030205218"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20521-8_72","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"16 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IWANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Work-Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gran Canaria","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 June 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 June 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwann2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iwann.uma.es\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"210","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"150","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"71% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2,9","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2,5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}