{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T02:32:27Z","timestamp":1783823547588,"version":"3.55.0"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T00:00:00Z","timestamp":1732924800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T00:00:00Z","timestamp":1732924800000},"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":["Appl Intell"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s10489-024-05896-y","type":"journal-article","created":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T05:52:07Z","timestamp":1732945927000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A cross-database micro-expression recognition framework based on meta-learning"],"prefix":"10.1007","volume":"55","author":[{"given":"Hanpu","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ju","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingjuan","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,30]]},"reference":[{"key":"5896_CR1","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.neucom.2014.01.029","volume":"136","author":"W Yan","year":"2014","unstructured":"Yan W, Wang S, Liu Y, Wu Q, Fu X (2014) For micro-expression recognition: Database and suggestions. Neurocomputing 136:82\u201387. https:\/\/doi.org\/10.1016\/j.neucom.2014.01.029","journal-title":"Neurocomputing"},{"issue":"24","key":"5896_CR2","doi-asserted-by":"publisher","first-page":"5553","DOI":"10.3390\/s19245553","volume":"19","author":"Y Zhao","year":"2019","unstructured":"Zhao Y, Xu J (2019) A convolutional neural network for compound micro-expression recognition. Sensors 19(24):5553. https:\/\/doi.org\/10.3390\/s19245553","journal-title":"Sensors"},{"key":"5896_CR3","doi-asserted-by":"publisher","first-page":"1833","DOI":"10.3389\/fpsyg.2019.01833","volume":"10","author":"G Zhao","year":"2019","unstructured":"Zhao G, Li X (2019) Automatic micro-expression analysis: open challenges. Front Psychol 10:1833. https:\/\/doi.org\/10.3389\/fpsyg.2019.01833","journal-title":"Front Psychol"},{"key":"5896_CR4","doi-asserted-by":"publisher","unstructured":"Pfister T, Li X, Zhao G, Pietik\u00e4inen M (2011) Recognising spontaneous facial micro-expressions. In: 2011 International Conference on Computer Vision, pp 1449\u20131456. https:\/\/doi.org\/10.1109\/ICCV.2011.6126401. IEEE","DOI":"10.1109\/ICCV.2011.6126401"},{"issue":"6","key":"5896_CR5","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1109\/TPAMI.2007.1110","volume":"29","author":"G Zhao","year":"2007","unstructured":"Zhao G, Pietikainen M (2007) Dynamic texture recognition using local binary patterns with an application to facial expressions. IEEE Trans Pattern Anal Mach Intell 29(6):915\u2013928. https:\/\/doi.org\/10.1109\/TPAMI.2007.1110","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"5896_CR6","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1109\/TAFFC.2015.2485205","volume":"7","author":"Y Liu","year":"2015","unstructured":"Liu Y, Zhang J, Yan W, Wang S, Zhao G, Fu X (2015) A main directional mean optical flow feature for spontaneous micro-expression recognition. IEEE Trans Affect Comput 7(4):299\u2013310. https:\/\/doi.org\/10.1109\/TAFFC.2015.2485205","journal-title":"IEEE Trans Affect Comput"},{"issue":"20","key":"5896_CR7","doi-asserted-by":"publisher","first-page":"23049","DOI":"10.1007\/s10489-023-04734-x","volume":"53","author":"Q Zhu","year":"2023","unstructured":"Zhu Q, Li Z, Kuang W, Ma H (2023) A multichannel location-aware interaction network for visual classification. Appl Intell 53(20):23049\u201323066. https:\/\/doi.org\/10.1007\/s10489-023-04734-x","journal-title":"Appl Intell"},{"key":"5896_CR8","doi-asserted-by":"publisher","first-page":"106928","DOI":"10.1016\/j.engappai.2023.106928","volume":"126","author":"X Yang","year":"2023","unstructured":"Yang X, Li Z, Zhong X, Zhang C, Ma H (2023) Mining graph-based dynamic relationships for object detection. Eng Appl Artif Intell 126:106928. https:\/\/doi.org\/10.1016\/j.engappai.2023.106928","journal-title":"Eng Appl Artif Intell"},{"key":"5896_CR9","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3313507","author":"G Lan","year":"2023","unstructured":"Lan G, Xiao S, Yang J, Zhou Y, Wen J, Lu W, Gao X (2023) Image aesthetics assessment based on hypernetwork of emotion fusion. IEEE Trans Multimedia. https:\/\/doi.org\/10.1109\/TMM.2023.3313507","journal-title":"IEEE Trans Multimedia"},{"key":"5896_CR10","doi-asserted-by":"publisher","unstructured":"Peng M, Wu Z, Zhang Z, Chen T (2018) From macro to micro expression recognition: Deep learning on small datasets using transfer learning. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp 657\u2013661. https:\/\/doi.org\/10.1109\/FG.2018.00103. IEEE","DOI":"10.1109\/FG.2018.00103"},{"key":"5896_CR11","doi-asserted-by":"publisher","unstructured":"Peng M, Wang C, Chen T (2018) Attention based residual network for micro-gesture recognition. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp 790\u2013794. https:\/\/doi.org\/10.1109\/FG.2018.00127. IEEE","DOI":"10.1109\/FG.2018.00127"},{"key":"5896_CR12","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.neucom.2020.06.005","volume":"410","author":"C Wang","year":"2020","unstructured":"Wang C, Peng M, Bi T, Chen T (2020) Micro-attention for micro-expression recognition. Neurocomputing. 410:354\u2013362. https:\/\/doi.org\/10.1016\/j.neucom.2020.06.005","journal-title":"Neurocomputing."},{"issue":"6","key":"5896_CR13","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2017) Imagenet classification with deep convolutional neural networks. Commun ACM 60(6):84\u201390. https:\/\/doi.org\/10.1145\/3065386","journal-title":"Commun ACM"},{"key":"5896_CR14","doi-asserted-by":"publisher","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 770\u2013778. https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"5896_CR15","doi-asserted-by":"publisher","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, Dehghani M, Minderer M, Heigold G, Gelly S, et al (2020) An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929. https:\/\/doi.org\/10.48550\/arXiv.2010.11929","DOI":"10.48550\/arXiv.2010.11929"},{"key":"5896_CR16","doi-asserted-by":"publisher","unstructured":"Khor H-Q, See J, Liong S-T, Phan RC, Lin W (2019) Dual-stream shallow networks for facial micro-expression recognition. In: 2019 IEEE International Conference on Image Processing (ICIP), pp 36\u201340. https:\/\/doi.org\/10.1109\/ICIP.2019.8802965. IEEE","DOI":"10.1109\/ICIP.2019.8802965"},{"issue":"4","key":"5896_CR17","doi-asserted-by":"publisher","first-page":"1973","DOI":"10.1109\/TAFFC.2022.3213509","volume":"13","author":"L Zhang","year":"2022","unstructured":"Zhang L, Hong X, Arandjelovi\u0107 O, Zhao G (2022) Short and long range relation based spatio-temporal transformer for micro-expression recognition. IEEE Trans Affect Comput 13(4):1973\u20131985. https:\/\/doi.org\/10.1109\/TAFFC.2022.3213509","journal-title":"IEEE Trans Affect Comput"},{"key":"5896_CR18","doi-asserted-by":"publisher","unstructured":"Nguyen X-B, Duong CN, Li X, Gauch S, Seo H-S, Luu K (2023) Micron-bert: Bert-based facial micro-expression recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 1482\u20131492. https:\/\/doi.org\/10.48550\/arXiv.2304.03195","DOI":"10.48550\/arXiv.2304.03195"},{"key":"5896_CR19","doi-asserted-by":"publisher","unstructured":"Yap MH, See J, Hong X, Wang S-J (2018) Facial micro-expressions grand challenge 2018 summary. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp 675\u2013678. https:\/\/doi.org\/10.1109\/FG.2018.00106. IEEE","DOI":"10.1109\/FG.2018.00106"},{"key":"5896_CR20","doi-asserted-by":"publisher","unstructured":"Xia B, Wang W, Wang S, Chen E (2020) Learning from macro-expression: A micro-expression recognition framework. In: Proceedings of the 28th ACM International Conference on Multimedia, pp 2936\u20132944. https:\/\/doi.org\/10.1145\/3394171.3413774","DOI":"10.1145\/3394171.3413774"},{"key":"5896_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2022.09.006","author":"Y Bao","year":"2024","unstructured":"Bao Y, Wu C, Zhang P, Shan C, Qi Y, Ben X (2024) Boosting micro-expression recognition via self-expression reconstruction and memory contrastive learning. IEEE Trans Affect Comput. https:\/\/doi.org\/10.1016\/j.patrec.2022.09.006","journal-title":"IEEE Trans Affect Comput"},{"key":"5896_CR22","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.image.2017.11.006","volume":"62","author":"S-T Liong","year":"2018","unstructured":"Liong S-T, See J, Wong K, Phan RC-W (2018) Less is more: Micro-expression recognition from video using apex frame. Signal Processing: Image Communication 62:82\u201392. https:\/\/doi.org\/10.1016\/j.image.2017.11.006","journal-title":"Signal Processing: Image Communication"},{"key":"5896_CR23","doi-asserted-by":"publisher","unstructured":"Li Y, Huang X, Zhao G (2018) Can micro-expression be recognized based on single apex frame? In: 2018 25th IEEE International Conference on Image Processing (ICIP), pp 3094\u20133098. https:\/\/doi.org\/10.1109\/ICIP.2018.8451376. IEEE","DOI":"10.1109\/ICIP.2018.8451376"},{"key":"5896_CR24","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1109\/TIP.2020.3035042","volume":"30","author":"Y Li","year":"2020","unstructured":"Li Y, Huang X, Zhao G (2020) Joint local and global information learning with single apex frame detection for micro-expression recognition. IEEE Trans Image Process 30:249\u2013263. https:\/\/doi.org\/10.1109\/TIP.2020.3035042","journal-title":"IEEE Trans Image Process"},{"issue":"14","key":"5896_CR25","doi-asserted-by":"publisher","first-page":"16621","DOI":"10.1007\/s10489-022-03284-y","volume":"52","author":"M-X Sun","year":"2022","unstructured":"Sun M-X, Liong S-T, Liu K-H, Wu Q-Q (2022) The heterogeneous ensemble of deep forest and deep neural networks for micro-expressions recognition. Appl Intell 52(14):16621\u201316639. https:\/\/doi.org\/10.1007\/s10489-022-03284-y","journal-title":"Appl Intell"},{"key":"5896_CR26","doi-asserted-by":"publisher","unstructured":"Zhou L, Mao Q, Xue L (2019) Dual-inception network for cross-database micro-expression recognition. In: 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019), pp 1\u20135. https:\/\/doi.org\/10.1109\/FG.2019.8756579. IEEE","DOI":"10.1109\/FG.2019.8756579"},{"key":"5896_CR27","doi-asserted-by":"publisher","first-page":"1345","DOI":"10.1109\/TMM.2022.3141616","volume":"25","author":"B Chen","year":"2022","unstructured":"Chen B, Liu K-H, Xu Y, Wu Q-Q, Yao J-F (2022) Block division convolutional network with implicit deep features augmentation for micro-expression recognition. IEEE Trans Multimed 25:1345\u20131358. https:\/\/doi.org\/10.1109\/TMM.2022.3141616","journal-title":"IEEE Trans Multimed"},{"key":"5896_CR28","doi-asserted-by":"publisher","unstructured":"Peng M, Wang C, Bi T, Shi Y, Zhou X, Chen T (2019) A novel apex-time network for cross-dataset micro-expression recognition. In: 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII), pp 1\u20136. https:\/\/doi.org\/10.1109\/ACII.2019.8925525. IEEE","DOI":"10.1109\/ACII.2019.8925525"},{"issue":"30","key":"5896_CR29","doi-asserted-by":"publisher","first-page":"43513","DOI":"10.1007\/s11042-022-12878-0","volume":"81","author":"J Liu","year":"2022","unstructured":"Liu J, Zong Y, Zheng W (2022) Cross-database micro-expression recognition based on transfer double sparse learning. Multimed Tools Appl 81(30):43513\u201343530. https:\/\/doi.org\/10.1007\/s11042-022-12878-0","journal-title":"Multimed Tools Appl"},{"issue":"5","key":"5896_CR30","doi-asserted-by":"publisher","first-page":"2484","DOI":"10.1109\/TIP.2018.2797479","volume":"27","author":"Y Zong","year":"2018","unstructured":"Zong Y, Zheng W, Huang X, Shi J, Cui Z, Zhao G (2018) Domain regeneration for cross-database micro-expression recognition. IEEE Trans Image Process 27(5):2484\u20132498. https:\/\/doi.org\/10.1109\/TIP.2018.2797479","journal-title":"IEEE Trans Image Process"},{"key":"5896_CR31","doi-asserted-by":"publisher","unstructured":"Lin W-W, Mak M-W, Li L, Chien J-T (2018) Reducing domain mismatch by maximum mean discrepancy based autoencoders. In: Odyssey, pp 162\u2013167. https:\/\/doi.org\/10.21437\/Odyssey.2018-23","DOI":"10.21437\/Odyssey.2018-23"},{"issue":"2","key":"5896_CR32","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1109\/TPAMI.2016.2544314","volume":"39","author":"T Liu","year":"2016","unstructured":"Liu T, Tao D, Song M, Maybank SJ (2016) Algorithm-dependent generalization bounds for multi-task learning. IEEE Trans Pattern Anal Mach Intell 39(2):227\u2013241. https:\/\/doi.org\/10.1109\/TPAMI.2016.2544314","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"5896_CR33","doi-asserted-by":"publisher","unstructured":"Grefenstette E, Amos B, Yarats D, Htut PM, Molchanov A, Meier F, Kiela D, Cho K, Chintala S (2019) Generalized inner loop meta-learning. arXiv preprint arXiv:1910.01727. https:\/\/doi.org\/10.48550\/arXiv.1910.01727","DOI":"10.48550\/arXiv.1910.01727"},{"key":"5896_CR34","doi-asserted-by":"publisher","unstructured":"Finn C, Levine S (2017) Meta-learning and universality: Deep representations and gradient descent can approximate any learning algorithm. arXiv preprint arXiv:1710.11622. https:\/\/doi.org\/10.48550\/arXiv.1710.11622","DOI":"10.48550\/arXiv.1710.11622"},{"issue":"9","key":"5896_CR35","doi-asserted-by":"publisher","first-page":"5149","DOI":"10.1109\/TPAMI.2021.3079209","volume":"44","author":"T Hospedales","year":"2021","unstructured":"Hospedales T, Antoniou A, Micaelli P, Storkey A (2021) Meta-learning in neural networks: A survey. IEEE Trans Pattern Anal Mach Intell 44(9):5149\u20135169. https:\/\/doi.org\/10.1109\/TPAMI.2021.3079209","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"5896_CR36","doi-asserted-by":"publisher","unstructured":"Guo Y, Codella NC, Karlinsky L, Codella JV, Smith JR, Saenko K, Rosing T, Feris R (2020) A broader study of cross-domain few-shot learning. In: Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XXVII 16, pp 124\u2013141. https:\/\/doi.org\/10.1007\/978-3-030-58583-9_8. Springer","DOI":"10.1007\/978-3-030-58583-9_8"},{"issue":"9","key":"5896_CR37","doi-asserted-by":"publisher","first-page":"5149","DOI":"10.1109\/TPAMI.2021.3079209","volume":"44","author":"T Hospedales","year":"2021","unstructured":"Hospedales T, Antoniou A, Micaelli P, Storkey A (2021) Meta-learning in neural networks: A survey. IEEE Trans Pattern Anal Mach Intell 44(9):5149\u20135169. https:\/\/doi.org\/10.1109\/TPAMI.2021.3079209","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"5896_CR38","doi-asserted-by":"publisher","unstructured":"Wan B, Dang J, Liu X, Wang Q (2022) Micro-expression recognition based on maml meta-learning algorithm. In: 2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld\/UIC\/ScalCom\/DigitalTwin\/PriComp\/Meta), pp 1322\u20131328. https:\/\/doi.org\/10.1109\/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00191. IEEE","DOI":"10.1109\/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00191"},{"key":"5896_CR39","doi-asserted-by":"publisher","unstructured":"Wang J, Tian Y, Yang Y, Chen X, Zheng C, Qiang W (2024) Meta-auxiliary learning for micro-expression recognition. arXiv preprint arXiv:2404.12024. https:\/\/doi.org\/10.48550\/arXiv.2404.12024","DOI":"10.48550\/arXiv.2404.12024"},{"issue":"2","key":"5896_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3539576","volume":"20","author":"W Gong","year":"2023","unstructured":"Gong W, Zhang Y, Wang W, Cheng P, Gonzalez J (2023) Meta-mmfnet: Meta-learning-based multi-model fusion network for micro-expression recognition. ACM Trans Multimed Comput Commun Appl 20(2):1\u201320. https:\/\/doi.org\/10.1145\/3539576","journal-title":"ACM Trans Multimed Comput Commun Appl"},{"issue":"2","key":"5896_CR41","doi-asserted-by":"publisher","first-page":"023014","DOI":"10.1117\/1.JEI.33.2.023014","volume":"33","author":"Z Wang","year":"2024","unstructured":"Wang Z, Fu W, Zhang Y, Li J, Gong W, Gonz\u00e0lez J (2024) Mcnet: meta-clustering learning network for micro-expression recognition. J Electron Imaging 33(2):023014\u2013023014. https:\/\/doi.org\/10.1117\/1.JEI.33.2.023014","journal-title":"J Electron Imaging"},{"key":"5896_CR42","doi-asserted-by":"publisher","first-page":"1575","DOI":"10.1109\/LSP.2021.3099076","volume":"28","author":"D Jia","year":"2021","unstructured":"Jia D, Wang K, Luo S, Liu T, Liu Y (2021) Braft: Recurrent all-pairs field transforms for optical flow based on correlation blocks. IEEE Signal Process Lett 28:1575\u20131579. https:\/\/doi.org\/10.1109\/LSP.2021.3099076","journal-title":"IEEE Signal Process Lett"},{"key":"5896_CR43","doi-asserted-by":"publisher","unstructured":"Rebuffi S-A, Bilen H, Vedaldi A (2017) Learning multiple visual domains with residual adapters. Adv Neural Inf Process Syst 30. https:\/\/doi.org\/10.5555\/3294771.3294820","DOI":"10.5555\/3294771.3294820"},{"key":"5896_CR44","doi-asserted-by":"publisher","unstructured":"Tseng H-Y, Lee H-Y, Huang J-B, Yang M-H (2020) Cross-domain few-shot classification via learned feature-wise transformation. arXiv preprint arXiv:2001.08735. https:\/\/doi.org\/10.48550\/arXiv.2001.08735","DOI":"10.48550\/arXiv.2001.08735"},{"key":"5896_CR45","doi-asserted-by":"publisher","unstructured":"Yan W, Wu Q, Liu Y, Wang S, Fu X (2013) Casme database: A dataset of spontaneous micro-expressions collected from neutralized faces. In: 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), pp 1\u20137. https:\/\/doi.org\/10.1109\/FG.2013.6553799. IEEE","DOI":"10.1109\/FG.2013.6553799"},{"issue":"1","key":"5896_CR46","doi-asserted-by":"publisher","first-page":"86041","DOI":"10.1371\/journal.pone.0086041","volume":"9","author":"W Yan","year":"2014","unstructured":"Yan W, Li X, Wang S, Zhao G, Liu Y, Chen Y-H, Fu X (2014) Casme ii: An improved spontaneous micro-expression database and the baseline evaluation. PLoS ONE 9(1):86041. https:\/\/doi.org\/10.1371\/journal.pone.0086041","journal-title":"PLoS ONE"},{"key":"5896_CR47","doi-asserted-by":"publisher","unstructured":"Ben X, Ren Y, Zhang J, Wang S-J, Kpalma K, Meng W, Liu Y-J (2021) Video-based facial micro-expression analysis: A survey of datasets, features and algorithms. IEEE Trans Pattern Anal Mach Intell 44(9):5826\u20135846. https:\/\/doi.org\/10.1109\/TPAMI.2021.3067464","DOI":"10.1109\/TPAMI.2021.3067464"},{"key":"5896_CR48","doi-asserted-by":"publisher","unstructured":"Li X, Pfister T, Huang X, Zhao G, Pietik\u00e4inen M (2013) A spontaneous micro-expression database: Inducement, collection and baseline. In: 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (fg), pp 1\u20136. https:\/\/doi.org\/10.1109\/FG.2013.6553717. IEEE","DOI":"10.1109\/FG.2013.6553717"},{"issue":"1","key":"5896_CR49","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1109\/TAFFC.2016.2573832","volume":"9","author":"AK Davison","year":"2016","unstructured":"Davison AK, Lansley C, Costen N, Tan K, Yap MH (2016) Samm: A spontaneous micro-facial movement dataset. IEEE Trans Affect Comput 9(1):116\u2013129. https:\/\/doi.org\/10.1109\/TAFFC.2016.2573832","journal-title":"IEEE Trans Affect Comput"},{"key":"5896_CR50","doi-asserted-by":"publisher","unstructured":"Yap MH, See J, Hong X, Wang S-J (2018) Facial micro-expressions grand challenge 2018 summary. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp 675\u2013678. https:\/\/doi.org\/10.1109\/FG.2018.00106. IEEE","DOI":"10.1109\/FG.2018.00106"},{"key":"5896_CR51","unstructured":"Maaten L, Hinton G (2008) Visualizing data using t-sne. J Mach Learn Res 9(11)"},{"key":"5896_CR52","doi-asserted-by":"publisher","unstructured":"Polikovsky S, Kameda Y, Ohta Y (2009) Facial micro-expressions recognition using high speed camera and 3d-gradient descriptor. https:\/\/doi.org\/10.1049\/ic.2009.0244","DOI":"10.1049\/ic.2009.0244"},{"key":"5896_CR53","doi-asserted-by":"publisher","unstructured":"Khor H-Q, See J, Phan RCW, Lin W (2018) Enriched long-term recurrent convolutional network for facial micro-expression recognition. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp 667\u2013674. https:\/\/doi.org\/10.1109\/FG.2018.00105. IEEE","DOI":"10.1109\/FG.2018.00105"},{"issue":"21","key":"5896_CR54","doi-asserted-by":"publisher","first-page":"11078","DOI":"10.3390\/app122111078","volume":"12","author":"KK Talluri","year":"2022","unstructured":"Talluri KK, Fiedler M-A, Al-Hamadi A (2022) Deep 3d convolutional neural network for facial micro-expression analysis from video images. Appl Sci 12(21):11078. https:\/\/doi.org\/10.3390\/app122111078","journal-title":"Appl Sci"},{"key":"5896_CR55","doi-asserted-by":"publisher","unstructured":"Zhang M, Huan Z, Shang L (2020) Micro-expression recognition using micro-variation boosted heat areas. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp 531\u2013543. https:\/\/doi.org\/10.1007\/978-3-030-60639-8_44. Springer","DOI":"10.1007\/978-3-030-60639-8_44"},{"issue":"3","key":"5896_CR56","doi-asserted-by":"publisher","first-page":"1593","DOI":"10.1007\/s00530-023-01068-z","volume":"29","author":"X Shu","year":"2023","unstructured":"Shu X, Li J, Shi L, Huang S (2023) Res-capsnet: an improved capsule network for micro-expression recognition. Multimed Syst 29(3):1593\u20131601. https:\/\/doi.org\/10.1007\/s00530-023-01068-z","journal-title":"Multimed Syst"},{"key":"5896_CR57","doi-asserted-by":"publisher","unstructured":"Peng M, Wu Z, Zhang Z, Chen T (2018) From macro to micro expression recognition: Deep learning on small datasets using transfer learning. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp 657\u2013661. https:\/\/doi.org\/10.1109\/FG.2018.00103. IEEE","DOI":"10.1109\/FG.2018.00103"},{"key":"5896_CR58","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.neucom.2020.06.005","volume":"410","author":"C Wang","year":"2020","unstructured":"Wang C, Peng M, Bi T, Chen T (2020) Micro-attention for micro-expression recognition. Neurocomputing 410:354\u2013362. https:\/\/doi.org\/10.1016\/j.neucom.2020.06.005","journal-title":"Neurocomputing"},{"issue":"02","key":"5896_CR59","doi-asserted-by":"publisher","first-page":"544","DOI":"10.1145\/3323873.3326590","volume":"34","author":"T Zhang","year":"2022","unstructured":"Zhang T, Zong Y, Zheng W, Chen CP, Hong X, Tang C, Cui Z, Zhao G (2022) Cross-database micro-expression recognition: A benchmark. IEEE Trans Knowl Data Eng 34(02):544\u2013559. https:\/\/doi.org\/10.1145\/3323873.3326590","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"4","key":"5896_CR60","doi-asserted-by":"publisher","first-page":"918","DOI":"10.3390\/math11040918","volume":"11","author":"Z Chen","year":"2023","unstructured":"Chen Z, Lu C, Zhou F, Zong Y (2023) Tkrm: Learning a transfer kernel regression model for cross-database micro-expression recognition. Mathematics 11(4):918. https:\/\/doi.org\/10.3390\/math11040918","journal-title":"Mathematics"},{"key":"5896_CR61","doi-asserted-by":"publisher","first-page":"123582","DOI":"10.1016\/j.eswa.2024.123582","volume":"249","author":"G Lan","year":"2024","unstructured":"Lan G, Xiao S, Yang J, Wen J, Lu W, Gao X (2024) Active learning inspired method in generative models. Expert Syst Appl 249:123582. https:\/\/doi.org\/10.1016\/j.eswa.2024.123582","journal-title":"Expert Syst Appl"},{"key":"5896_CR62","doi-asserted-by":"publisher","unstructured":"Lan G, Xiao S, Yang J, Wen J, Xi M (2023) Generative ai-based data completeness augmentation algorithm for data-driven smart healthcare. IEEE J Biomed Health Inform. https:\/\/doi.org\/10.1109\/JBHI.2023.3327485","DOI":"10.1109\/JBHI.2023.3327485"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05896-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-05896-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05896-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T15:14:52Z","timestamp":1735830892000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-05896-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,30]]},"references-count":62,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["5896"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-05896-y","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,30]]},"assertion":[{"value":"25 October 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 November 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no conflicts of interest to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical and informed consent for data used"}}],"article-number":"58"}}