{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T23:40:22Z","timestamp":1743118822706,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030869922"},{"type":"electronic","value":"9783030869939"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-86993-9_14","type":"book-chapter","created":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T23:08:06Z","timestamp":1631660886000},"page":"146-156","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Emojis Pictogram Classification for\u00a0Semantic Recognition of\u00a0Emotional Context"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3460-7164","authenticated-orcid":false,"given":"Muhammad","family":"Atif","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2972-7188","authenticated-orcid":false,"given":"Valentina","family":"Franzoni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4534-1805","authenticated-orcid":false,"given":"Alfredo","family":"Milani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,15]]},"reference":[{"key":"14_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"986","DOI":"10.1007\/978-3-540-39964-3_62","volume-title":"On The Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE","author":"G Guo","year":"2003","unstructured":"Guo, G., Wang, H., Bell, D., Bi, Y., Greer, K.: KNN model-based approach in classification. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) OTM 2003. LNCS, vol. 2888, pp. 986\u2013996. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/978-3-540-39964-3_62"},{"issue":"2","key":"14_CR2","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1109\/72.991427","volume":"13","author":"H Chih-Wei","year":"2002","unstructured":"Chih-Wei, H., Chih-Jen, L.: A comparison of methods for multiclass support vector machines. IEEE Trans. Neural Netw. 13(2), 415\u2013425 (2002)","journal-title":"IEEE Trans. Neural Netw."},{"key":"14_CR3","unstructured":"Mitchell, T.M.: Machine learning (1997)"},{"key":"14_CR4","unstructured":"\u015eener, B., \u00c7okluk-B\u00f6keo\u011flu, \u00d6.: Discriminant function analysis: concept and application. Eurasian J. Educ. Res. (EJER) 33, 73\u201392 (2008)"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Li, W., Li, D., Zeng, S.: Traffic Sign Recognition with a small convolutional neural network. In: IOP, vol. 688, no. 4 (2019)","DOI":"10.1088\/1757-899X\/688\/4\/044034"},{"key":"14_CR6","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, vol. 25, pp. 1097\u20131105 (2012)"},{"key":"14_CR7","doi-asserted-by":"crossref","unstructured":"Sahoo, J., Prakash, S.A., Patra, S.K.: Hand gesture recognition using PCA based deep CNN reduced features and SVM classifier. In: IEEE International Symposium on Smart Electronic Systems (iSES), pp. 221\u2013224 (2019)","DOI":"10.1109\/iSES47678.2019.00056"},{"issue":"3\u20134","key":"14_CR8","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1080\/02699939208411068","volume":"6","author":"P Ekman","year":"1992","unstructured":"Ekman, P.: An argument for basic emotions. Cogn. Emot. 6(3\u20134), 169\u2013200 (1992)","journal-title":"Cogn. Emot."},{"key":"14_CR9","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.patrec.2019.01.008","volume":"120","author":"DK Jain","year":"2019","unstructured":"Jain, D.K., Shamsolmoali, P., Sehdev, P.: Extended deep neural network for facial emotion recognition. Pattern Recogn. Lett. 120, 69\u201374 (2019)","journal-title":"Pattern Recogn. Lett."},{"issue":"7","key":"14_CR10","doi-asserted-by":"publisher","first-page":"1319","DOI":"10.1109\/TMM.2016.2557721","volume":"18","author":"J Yan","year":"2016","unstructured":"Yan, J., Wenming, Z., et al.: Sparse kernel reduced-rank regression for bimodal emotion recognition from facial expression and speech. IEEE Trans. Multimed. 18(7), 1319\u20131329 (2016)","journal-title":"IEEE Trans. Multimed."},{"key":"14_CR11","unstructured":"Martin, W., Metallinou, A., et al.: Context-sensitive multimodal emotion recognition from speech and facial expression using bidirectional LSTM modeling. In: Proceedings of INTERSPEECH, pp. 2362\u20132365 (2010)"},{"key":"14_CR12","unstructured":"Liu, X., Fan, F., et al.: Image2Audio: facilitating semi-supervised audio emotion recognition with facial expression image. In: Proceedings of the IEEE\/CVF, pp. 912\u2013913 (2020)"},{"key":"14_CR13","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., et al.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Liu, W., et al.: Going deeper with convolutions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20139 (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"14_CR15","unstructured":"Ba, J.L., et al.: Adam: a method for stochastic gradient descent. In: ICLR, pp. 1\u201315 (2015)"},{"key":"14_CR16","unstructured":"Liu, Y., Gao, Y., Yin, W.: An improved analysis of stochastic gradient descent with momentum. arXiv preprint arXiv:2007.07989 (2020)"},{"issue":"18","key":"14_CR17","doi-asserted-by":"publisher","first-page":"5222","DOI":"10.3390\/s20185222","volume":"20","author":"V Franzoni","year":"2020","unstructured":"Franzoni, V., Biondi, G., Perri, D., Gervasi, O.: Enhancing mouth-based emotion recognition using transfer learning. Sensors 20(18), 5222 (2020)","journal-title":"Sensors"},{"issue":"1","key":"14_CR18","doi-asserted-by":"publisher","first-page":"17","DOI":"10.3233\/WEB-190397","volume":"17","author":"O Gervasi","year":"2019","unstructured":"Gervasi, O., Franzoni, V., Riganelli, M., Tasso, S.: Automating facial emotion recognition. Web Intell. 17(1), 17\u201327 (2019)","journal-title":"Web Intell."}],"container-title":["Lecture Notes in Computer Science","Brain Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86993-9_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T23:42:02Z","timestamp":1631662922000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86993-9_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030869922","9783030869939"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86993-9_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"15 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Brain Informatics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"brain2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/bi2021.org\/","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":"90","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":"49","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":"2","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":"54% - 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":"4","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)"}}]}}