{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T07:38:53Z","timestamp":1742974733432,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031430770"},{"type":"electronic","value":"9783031430787"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-43078-7_13","type":"book-chapter","created":{"date-parts":[[2023,9,30]],"date-time":"2023-09-30T18:02:23Z","timestamp":1696096943000},"page":"157-168","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AATiENDe: Automatic ATtention Evaluation on\u00a0a\u00a0Non-invasive Device"],"prefix":"10.1007","author":[{"given":"Felix","family":"Escalona","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco","family":"Gomez-Donoso","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco","family":"Morillas-Espejo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Monica","family":"Pina-Navarro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis","family":"Marquez-Carpintero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel","family":"Cazorla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,1]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","unstructured":"Bosch, N.: Detecting student engagement: human versus machine. In: Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, UMAP \u201916, pp. 317\u2013320. Association for Computing Machinery, New York, NY, USA (2016). https:\/\/doi.org\/10.1145\/2930238.2930371","DOI":"10.1145\/2930238.2930371"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Barbadekar, A., et al.: Engagement index for classroom lecture using computer vision. In: Global Conference for Advancement in Technology (GCAT), 2019, pp. 1\u20135 (2019)","DOI":"10.1109\/GCAT47503.2019.8978355"},{"key":"13_CR3","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1007\/978-3-319-94779-2_32","volume-title":"Highlights of Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection","author":"D Canedo","year":"2018","unstructured":"Canedo, D., Trifan, A., Neves, A.J.R.: Monitoring students\u2019 attention in a classroom through computer vision. In: Bajo, J., et al. (eds.) PAAMS 2018. CCIS, vol. 887, pp. 371\u2013378. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-94779-2_32"},{"key":"13_CR4","doi-asserted-by":"crossref","unstructured":"Li, W., Jiang, F., Shen, R.: Sleep gesture detection in classroom monitor system. In: ICASSP 2019\u20132019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7640\u20137644 (2019)","DOI":"10.1109\/ICASSP.2019.8683116"},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Dinesh, A.N.S.D., Bijlani, K.: Student analytics for productive teaching\/learning. In: 2016 International Conference on Information Science (ICIS), pp. 97\u2013102 (2016)","DOI":"10.1109\/INFOSCI.2016.7845308"},{"issue":"2","key":"13_CR6","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","volume":"57","author":"P Viola","year":"2004","unstructured":"Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vision 57(2), 137\u2013154 (2004)","journal-title":"Int. J. Comput. Vision"},{"issue":"7","key":"13_CR7","doi-asserted-by":"publisher","first-page":"1409","DOI":"10.1109\/TPAMI.2011.239","volume":"34","author":"Z Kalal","year":"2011","unstructured":"Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE Trans. Pattern Anal. Mach. Intell. 34(7), 1409\u20131422 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"13_CR8","doi-asserted-by":"crossref","unstructured":"Martin, S., Tran, C., Trivedi, M.: Optical flow based head movement and gesture analyzer (ohmega). In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), pp. 605\u2013608. IEEE (2012)","DOI":"10.1109\/ITSC.2012.6338909"},{"key":"13_CR9","doi-asserted-by":"publisher","unstructured":"Liao, W., Xu, W., Kong, S., Ahmad, F., Liu, W.: A two-stage method for hand-raising gesture recognition in classroom, pp. 38\u201344 (2019). https:\/\/doi.org\/10.1145\/3318396.3318437","DOI":"10.1145\/3318396.3318437"},{"key":"13_CR10","doi-asserted-by":"crossref","unstructured":"Selim, T., Elkabani, I., Abdou, M.A.: Students engagement level detection in online e-learning using hybrid efficientnetb7 together with TCN, LSTM, and Bi-LSTM. IEEE Access 10, 99:573\u201399:583 (2022)","DOI":"10.1109\/ACCESS.2022.3206779"},{"key":"13_CR11","unstructured":"Tan, M., Le, Q.: Efficientnet: rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning, pp. 6105\u20136114. PMLR (2019)"},{"issue":"8","key":"13_CR12","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"issue":"11","key":"13_CR13","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster, M., Paliwal, K.K.: Bidirectional recurrent neural networks. IEEE Trans. Sig. Process. 45(11), 2673\u20132681 (1997)","journal-title":"IEEE Trans. Sig. Process."},{"key":"13_CR14","unstructured":"Bai, S., Kolter, J.Z., Koltun, V.: An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271 (2018)"},{"key":"13_CR15","doi-asserted-by":"crossref","unstructured":"Christian Mejia-Escobar, E.M.-M., Cazorla, M.: Towards a better performance in facial expression recognition: a data-centric approach. In: Computational Intelligence and Neuroscience (2023)","DOI":"10.1155\/2023\/1394882"},{"key":"13_CR16","unstructured":"Bhallaakshit: Facial expression recognition, September 2020. https:\/\/www.kaggle.com\/code\/bhallaakshit\/facial-expression-recognition\/notebook"},{"issue":"1","key":"13_CR17","first-page":"173","volume":"4","author":"S Suwarno","year":"2020","unstructured":"Suwarno, S., Kevin, K.: Analysis of face recognition algorithm: Dlib and OpenCV. J. Inform. Telecommun. Eng. 4(1), 173\u2013184 (2020)","journal-title":"J. Inform. Telecommun. Eng."},{"key":"13_CR18","doi-asserted-by":"crossref","unstructured":"Kazemi, V., Sullivan, J.: One millisecond face alignment with an ensemble of regression trees. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 1867\u20131874 (2014)","DOI":"10.1109\/CVPR.2014.241"},{"key":"13_CR19","doi-asserted-by":"publisher","unstructured":"Valentin\u00a0Bazarevsky, E.G.B., Grishchenko, I.: Blazepose: on-device real-time body pose tracking. In: CVPR Workshop on Computer Vision for Augmented and Virtual Reality. ACM, August 2020. https:\/\/doi.org\/10.1145\/2F2939672.2939785","DOI":"10.1145\/2F2939672.2939785"},{"key":"13_CR20","unstructured":"Lugaresi, C., et al.: Mediapipe: a framework for building perception pipelines (2019). https:\/\/arxiv.org\/abs\/1906.08172"},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: XGBoost. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, August 2016. https:\/\/doi.org\/10.1145\/2F2939672.2939785","DOI":"10.1145\/2939672.2939785"},{"key":"13_CR22","first-page":"3146","volume":"30","author":"G Ke","year":"2017","unstructured":"Ke, G., et al.: LightGBM: a highly efficient gradient boosting decision tree. Adv. Neural. Inf. Process. Syst. 30, 3146\u20133154 (2017)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"2","key":"13_CR23","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou, H., Hastie, T.: Regularization and variable selection via the elastic net. J. Roy. Stat. Soc. Ser. B (Stat. Methodol.) 67(2), 301\u2013320 (2005)","journal-title":"J. Roy. Stat. Soc. Ser. B (Stat. Methodol.)"},{"issue":"4","key":"13_CR24","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/BF02478259","volume":"5","author":"WS McCulloch","year":"1943","unstructured":"McCulloch, W.S., Pitts, W.: A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 5(4), 115\u2013133 (1943)","journal-title":"Bull. Math. Biophys."},{"issue":"3","key":"13_CR25","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","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."},{"issue":"5","key":"13_CR26","doi-asserted-by":"publisher","first-page":"2612","DOI":"10.1109\/TCSVT.2021.3061719","volume":"32","author":"V Delvigne","year":"2022","unstructured":"Delvigne, V., Wannous, H., Dutoit, T., Ris, L., Vandeborre, J.-P.: Phydaa: physiological dataset assessing attention. IEEE Trans. Circuits Syst. Video Technol. 32(5), 2612\u20132623 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"13_CR27","doi-asserted-by":"crossref","unstructured":"Chong, E., Wang, Y., Ruiz, N., Rehg, J.M.: Detecting attended visual targets in video. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2020","DOI":"10.1109\/CVPR42600.2020.00544"},{"key":"13_CR28","doi-asserted-by":"crossref","unstructured":"Fan, S., et al.: Emotional attention: a study of image sentiment and visual attention. In:. IEEE\/CVF Conference on Computer Vision and Pattern Recognition 2018, pp. 7521\u20137531 (2018)","DOI":"10.1109\/CVPR.2018.00785"}],"container-title":["Lecture Notes in Computer Science","Advances in Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43078-7_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,23]],"date-time":"2023-12-23T04:03:19Z","timestamp":1703304199000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43078-7_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031430770","9783031430787"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43078-7_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"1 October 2023","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":"Ponta Delgada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 June 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 June 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwann2023","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 (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":"149","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":"108","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":"72% - 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":"2,7","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":"2","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)"}}]}}