{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T15:58:33Z","timestamp":1743091113915,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030377335"},{"type":"electronic","value":"9783030377342"}],"license":[{"start":{"date-parts":[[2019,12,24]],"date-time":"2019-12-24T00:00:00Z","timestamp":1577145600000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-37734-2_39","type":"book-chapter","created":{"date-parts":[[2019,12,26]],"date-time":"2019-12-26T19:03:00Z","timestamp":1577386980000},"page":"475-486","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Experiences and Insights from the Collection of a Novel Multimedia EEG Dataset"],"prefix":"10.1007","author":[{"given":"Graham","family":"Healy","sequence":"first","affiliation":[]},{"given":"Zhengwei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Tomas","family":"Ward","sequence":"additional","affiliation":[]},{"given":"Alan","family":"Smeaton","sequence":"additional","affiliation":[]},{"given":"Cathal","family":"Gurrin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,12,24]]},"reference":[{"issue":"2","key":"39_CR1","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/S0167-8760(99)00070-7","volume":"34","author":"JY Bennington","year":"1999","unstructured":"Bennington, J.Y., Polich, J.: Comparison of p300 from passive and active tasks for auditory and visual stimuli. Int. J. Psychophysiol. 34(2), 171\u2013177 (1999)","journal-title":"Int. J. Psychophysiol."},{"issue":"11\u201312","key":"39_CR2","doi-asserted-by":"publisher","first-page":"682","DOI":"10.5694\/j.1326-5377.2009.tb03379.x","volume":"191","author":"JS Furyk","year":"2009","unstructured":"Furyk, J.S., O\u2019Kane, C.J., Aitken, P.J., Banks, C.J., Kault, D.A.: Fast versus slow bandaid removal: a randomised trial. Med. J. Aust. 191(11\u201312), 682\u2013683 (2009)","journal-title":"Med. J. Aust."},{"key":"39_CR3","doi-asserted-by":"publisher","first-page":"267","DOI":"10.3389\/fnins.2013.00267","volume":"7","author":"A Gramfort","year":"2013","unstructured":"Gramfort, A., et al.: MEG and EEG data analysis with MNE-python. Front. Neurosci. 7, 267 (2013)","journal-title":"Front. Neurosci."},{"key":"39_CR4","doi-asserted-by":"crossref","unstructured":"Gurrin, C., Joho, H., Hopfgartner, F., Zhou, L., Albatal, R.: NTCIR Lifelog: the first test collection for lifelog research. In: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 705\u2013708. ACM (2016)","DOI":"10.1145\/2911451.2914680"},{"key":"39_CR5","doi-asserted-by":"crossref","unstructured":"Healy, G., Smeaton, A.F.: Eye fixation related potentials in a target search task. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4203\u20134206, August 2011","DOI":"10.1109\/IEMBS.2011.6091043"},{"key":"39_CR6","unstructured":"Healy, G., Wang, Z., Currin, C., Ward, T.E., Smeaton, A.F.: An EEG image-search dataset: a first-of-its-kind in IR\/IIR. NAILS: neurally augmented image labelling strategies. In: Proceedings of CHIR Workshop on Challenges in Bringing Neuroscience to Research in Human-Information Interaction, Oslo, Norway, 11 March 2017"},{"key":"39_CR7","unstructured":"Healy, G., Ward, T.E., Gurrin, C., Smeaton, A.F.: Overview of NTCIR-13 NAILS task (2017)"},{"key":"39_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1007\/978-3-319-27674-8_28","volume-title":"MultiMedia Modeling","author":"GF Healy","year":"2016","unstructured":"Healy, G.F., Gurrin, C., Smeaton, A.F.: Informed perspectives on human annotation using neural signals. In: Tian, Q., Sebe, N., Qi, G.-J., Huet, B., Hong, R., Liu, X. (eds.) MMM 2016. LNCS, vol. 9517, pp. 315\u2013327. Springer, Cham (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-319-27674-8_28"},{"key":"39_CR9","unstructured":"Hutson, H., Geva, S., Cimiano, P.: Ensemble methods for the NTCIR-13 NAILS task. In: Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies, NTCIR-13, Tokyo, Japan, 5\u20138 December 2017 (2017)"},{"key":"39_CR10","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.neuroimage.2018.09.012","volume":"184","author":"JW Kam","year":"2019","unstructured":"Kam, J.W., et al.: Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes. NeuroImage 184, 119\u2013129 (2019)","journal-title":"NeuroImage"},{"key":"39_CR11","doi-asserted-by":"crossref","unstructured":"Koelstra, S., et al.: Deap: a database for emotion analysis using physiological signals 3(1), 18\u201331 (2012). eemcs-eprint-21368","DOI":"10.1109\/T-AFFC.2011.15"},{"issue":"5","key":"39_CR12","doi-asserted-by":"publisher","first-page":"056013","DOI":"10.1088\/1741-2552\/aace8c","volume":"15","author":"VJ Lawhern","year":"2018","unstructured":"Lawhern, V.J., Solon, A.J., Waytowich, N.R., Gordon, S.M., Hung, C.P., Lance, B.J.: Eegnet: a compact convolutional neural network for EEG-based brain-computer interfaces. J. Neural Eng. 15(5), 056013 (2018)","journal-title":"J. Neural Eng."},{"key":"39_CR13","unstructured":"Luck, S.J.: An Introduction to the Event-related Potential Technique. MIT Press (2014)"},{"key":"39_CR14","doi-asserted-by":"publisher","first-page":"270","DOI":"10.3389\/fnins.2015.00270","volume":"9","author":"AR Marathe","year":"2015","unstructured":"Marathe, A.R., et al.: The effect of target and non-target similarity on neural classification performance: a boost from confidence. Front. Neurosci. 9, 270 (2015)","journal-title":"Front. Neurosci."},{"issue":"1","key":"39_CR15","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1111\/psyp.12536","volume":"54","author":"KE Mathewson","year":"2017","unstructured":"Mathewson, K.E., Harrison, T.J., Kizuk, S.A.: High and dry? Comparing active dry eeg electrodes to active and passive wet electrodes. Psychophysiology 54(1), 74\u201382 (2017)","journal-title":"Psychophysiology"},{"issue":"11","key":"39_CR16","doi-asserted-by":"publisher","first-page":"2553","DOI":"10.1109\/TBME.2015.2481482","volume":"62","author":"TR Mullen","year":"2015","unstructured":"Mullen, T.R., et al.: Real-time neuroimaging and cognitive monitoring using wearable dry EEG. IEEE Trans. Biomed. Eng. 62(11), 2553\u20132567 (2015)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"39_CR17","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"39_CR18","doi-asserted-by":"publisher","first-page":"036025","DOI":"10.1088\/1741-2560\/8\/3\/036025","volume":"8","author":"EA Pohlmeyer","year":"2011","unstructured":"Pohlmeyer, E.A., et al.: Closing the loop in cortically-coupled computer vision: a brain-computer interface for searching image databases. J. Neural Eng. 8(3), 036025 (2011)","journal-title":"J. Neural Eng."},{"issue":"10","key":"39_CR19","doi-asserted-by":"publisher","first-page":"2128","DOI":"10.1016\/j.clinph.2007.04.019","volume":"118","author":"J Polich","year":"2007","unstructured":"Polich, J.: Updating P300: an integrative theory of P3a and P3b. Clin. Neurophysiol. 118(10), 2128\u20132148 (2007)","journal-title":"Clin. Neurophysiol."},{"key":"39_CR20","doi-asserted-by":"publisher","first-page":"557","DOI":"10.3389\/fnhum.2014.00557","volume":"8","author":"A Ramchurn","year":"2014","unstructured":"Ramchurn, A., de Fockert, J.W., Mason, L., Darling, S., Bunce, D.: Intraindividual reaction time variability affects p300 amplitude rather than latency. Front. Hum. Neurosci. 8, 557 (2014)","journal-title":"Front. Hum. Neurosci."},{"key":"39_CR21","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.jvcir.2015.11.002","volume":"34","author":"S Razakarivony","year":"2016","unstructured":"Razakarivony, S., Jurie, F.: Vehicle detection in aerial imagery : a small target detection benchmark. J. Vis. Commun. Image Representation 34, 187\u2013203 (2016)","journal-title":"J. Vis. Commun. Image Representation"},{"issue":"3","key":"39_CR22","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., et al.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vis. (IJCV) 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"key":"39_CR23","unstructured":"Smeaton, A.F., et al.: Dublin\u2019s participation in the predicting media memorability task at mediaeval 2018 (2018)"},{"key":"39_CR24","unstructured":"Solon, A.J., Gordon, S.M., Lance, B.J., Lawhern, V.J.: Deep Learning Approaches for P300 classification in image triage: applications to the NAILS task. In: Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies, NTCIR-13, Tokyo, Japan, 5\u20138 December 2017 (2017)"},{"key":"39_CR25","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1038\/381520a0","volume":"381","author":"S Thorpe","year":"1996","unstructured":"Thorpe, S., Fize, D., Marlot, C.: Speed of processing in the human visual system. Nature 381, 520 (1996)","journal-title":"Nature"},{"key":"39_CR26","unstructured":"Wang, Z., Healy, G., Smeaton, A.F., Ward, T.E.: An investigation of triggering approaches for the rapid serial visual presentation paradigm in brain computer interfacing. In: 2016 27th Irish Signals and Systems Conference (ISSC), pp. 1\u20136. IEEE (2016)"},{"key":"39_CR27","doi-asserted-by":"crossref","unstructured":"Wang, Z., Healy, G., Smeaton, A.F., Ward, T.E.: Use of neural signals to evaluate the quality of generative adversarial network performance in facial image generation. Cognitive Computation, August 2019","DOI":"10.1007\/s12559-019-09670-y"},{"key":"39_CR28","unstructured":"Zhou, B., Khosla, A., Lapedriza, A., Torralba, A., Oliva, A.: Places: an image database for deep scene understanding. CoRR, abs\/1610.02055 (2016)"}],"container-title":["Lecture Notes in Computer Science","MultiMedia Modeling"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-37734-2_39","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T13:12:07Z","timestamp":1580994727000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-37734-2_39"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,24]]},"ISBN":["9783030377335","9783030377342"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-37734-2_39","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019,12,24]]},"assertion":[{"value":"24 December 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MMM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Multimedia Modeling","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Daejeon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 January 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 January 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mmm2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mmm2020.kr\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"171","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23% - 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 (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Of the 171 submissions, 46 were accepted as poster papers; of the 49 special session paper submissions, 28 were accepted for oral presentation and 8 for poster presentation; 9 demo papers and 10 VBS papers were also accepted.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}