{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T18:17:40Z","timestamp":1783966660436,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the Fundamental Research Funds for the Central Universities","award":["2020YJS025"],"award-info":[{"award-number":["2020YJS025"]}]},{"name":"National Natural Science Foundation of China","award":["61603029"],"award-info":[{"award-number":["61603029"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3413724","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T13:12:00Z","timestamp":1602508320000},"page":"2909-2917","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":149,"title":["SST-EmotionNet: Spatial-Spectral-Temporal based Attention 3D Dense Network for EEG Emotion Recognition"],"prefix":"10.1145","author":[{"given":"Ziyu","family":"Jia","sequence":"first","affiliation":[{"name":"Beijing Jiaotong University & Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youfang","family":"Lin","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University & Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiyang","family":"Cai","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haobin","family":"Chen","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haijun","family":"Gou","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University & Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2016.10.021"},{"issue":"10","key":"e_1_3_2_2_2_1","first-page":"355","article-title":"Emotion recognition based on eeg using lstm recurrent neural network","volume":"8","author":"Alhagry Salma","year":"2017","journal-title":"Emotion"},{"key":"e_1_3_2_2_3_1","first-page":"01","article-title":"Classification of human emotions from electroencephalogram (eeg) signal using deep neural network","volume":"8","author":"Alnafjan Abeer","year":"2017","journal-title":"International Journal of Advanced Computer Science and Applications"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICBME.2013.6782224"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucli.2017.01.009"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/NER.2013.6695876"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70096-0_73"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/titb.2010.2041553"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1364\/JOSA.55.000247"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.3390\/e21121233"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.101.062113"},{"key":"e_1_3_2_2_13_1","first-page":"1324","volume-title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020","author":"Jia Ziyu","year":"2020"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"crossref","unstructured":"Yann LeCun Yoshua Bengio and Geoffrey Hinton. Deep learning. nature 521(7553):436--444 2015.  Yann LeCun Yoshua Bengio and Geoffrey Hinton. Deep learning. nature 521(7553):436--444 2015.","DOI":"10.1038\/nature14539"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-017-9533-x"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/NER.2019.8716943"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/216"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2019.2922912"},{"key":"e_1_3_2_2_19_1","unstructured":"Yang Li Wenming Zheng Lei Wang Yuan Zong Lei Qi Zhen Cui Tong Zhang and Tengfei Song. A novel bi-hemispheric discrepancy model for eeg emotion recognition. arXiv preprint arXiv:1906.01704 2019.  Yang Li Wenming Zheng Lei Wang Yuan Zong Lei Qi Zhen Cui Tong Zhang and Tengfei Song. A novel bi-hemispheric discrepancy model for eeg emotion recognition. arXiv preprint arXiv:1906.01704 2019."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2010.2048568"},{"key":"e_1_3_2_2_21_1","first-page":"101","volume-title":"Transactions on computational science XVIII","author":"Liu Yisi","year":"2013"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350871"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.590"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2019.2916015"},{"key":"e_1_3_2_2_25_1","article-title":"Eeg emotion recognition using dynamical graph convolutional neural networks","author":"Song Tengfei","year":"2018","journal-title":"IEEE Transactions on Affective Computing"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Johan AK Suykens and Joos Vandewalle. Least squares support vector machine classifiers. Neural processing letters 9(3):293--300 1999.  Johan AK Suykens and Joos Vandewalle. Least squares support vector machine classifiers. Neural processing letters 9(3):293--300 1999.","DOI":"10.1023\/A:1018628609742"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-24955-6_87"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2017.2685338"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2019.2937768"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"crossref","unstructured":"Wei-Long Zheng Wei Liu Yifei Lu Bao-Liang Lu and Andrzej Cichocki. Emotionmeter: A multimodal framework for recognizing human emotions. IEEE transactions on cybernetics 49(3):1110--1122 2018.  Wei-Long Zheng Wei Liu Yifei Lu Bao-Liang Lu and Andrzej Cichocki. Emotionmeter: A multimodal framework for recognizing human emotions. IEEE transactions on cybernetics 49(3):1110--1122 2018.","DOI":"10.1109\/TCYB.2018.2797176"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAMD.2015.2431497"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2014.6890166"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2016.2587290"},{"key":"e_1_3_2_2_34_1","unstructured":"Peixiang Zhong Di Wang and Chunyan Miao. Eeg-based emotion recognition using regularized graph neural networks. arXiv preprint arXiv:1907.07835 2019.  Peixiang Zhong Di Wang and Chunyan Miao. Eeg-based emotion recognition using regularized graph neural networks. arXiv preprint arXiv:1907.07835 2019."},{"key":"e_1_3_2_2_35_1","first-page":"1295","volume-title":"Proceedings of the 27th ACM International Conference on Multimedia","author":"Fares Ahmed","year":"2019"}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","location":"Seattle WA USA","acronym":"MM '20","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413724","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3413724","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:01:16Z","timestamp":1750197676000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413724"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":35,"alternative-id":["10.1145\/3394171.3413724","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3413724","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}