{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T08:26:11Z","timestamp":1770279971913,"version":"3.49.0"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,15]]},"DOI":"10.1109\/bigdata52589.2021.9671925","type":"proceedings-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T20:39:16Z","timestamp":1642106356000},"page":"1999-2008","source":"Crossref","is-referenced-by-count":24,"title":["Soft Sensing Transformer: Hundreds of Sensors are Worth a Single Word"],"prefix":"10.1109","author":[{"given":"Chao","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Jaswanth","family":"Yella","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Xiaoye","family":"Qian","sequence":"additional","affiliation":[]},{"given":"Sergei","family":"Petrov","sequence":"additional","affiliation":[]},{"given":"Andrey","family":"Rzhetsky","sequence":"additional","affiliation":[]},{"given":"Sthitie","family":"Bom","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","article-title":"Tensorflow: Large-scale machine learning on heterogeneous distributed systems","author":"abadi","year":"2016"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2005.10.010"},{"key":"ref31","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref30","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"key":"ref35","article-title":"Auto-encoder based model for highdimensional imbalanced industrial data","author":"zhang","year":"2021"},{"key":"ref34","article-title":"Keras","author":"chollet","year":"2015"},{"key":"ref10","article-title":"Prognostics with variational autoencoder by generative adversarial learning","author":"huang","year":"2021","journal-title":"IEEE Transactions on Industrial Electronics"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2969709"},{"key":"ref12","article-title":"Novel transformer based on gated convolutional neural network for dynamic soft sensor modeling of industrial processes","author":"geng","year":"2021","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2013.09.014"},{"key":"ref14","volume":"22","author":"fortuna","year":"2007","journal-title":"Soft Sensors for Monitoring and Control of Industrial Processes"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref16","first-page":"59986008","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref17","article-title":"Bert: Pretraining of deep bidirectional transformers for language understanding","author":"devlin","year":"2018"},{"key":"ref18","article-title":"A survey of transformers","author":"lin","year":"2021"},{"key":"ref19","article-title":"A survey on visual transformer","author":"han","year":"2020"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref27","first-page":"7482","article-title":"Multi-task learning using uncertainty to weigh losses for scene geometry and semantics","author":"kendall","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref3","article-title":"Information processing in dynamical systems: Foundations of harmony theory","author":"smolensky","year":"1986","journal-title":"Tech Rep"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2938890"},{"key":"ref29","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"ICML"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/323533a0"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.2988667"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-34833-5_4"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.09.055"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.5762"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3053128"},{"key":"ref20","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020"},{"key":"ref22","article-title":"Scaling vision transformers","author":"zhai","year":"2021"},{"key":"ref21","doi-asserted-by":"crossref","DOI":"10.1109\/ICCV48922.2021.00986","article-title":"Swin transformer: Hierarchical vision transformer using shifted windows","author":"liu","year":"2021"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/BigData52589.2021.9671903"},{"key":"ref23","author":"fukunada","year":"1990","journal-title":"Introduction to statistical pattern recognition"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/BigData52589.2021.9671850"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/BigData52589.2021.9671991"}],"event":{"name":"2021 IEEE International Conference on Big Data (Big Data)","location":"Orlando, FL, USA","start":{"date-parts":[[2021,12,15]]},"end":{"date-parts":[[2021,12,18]]}},"container-title":["2021 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9671263\/9671273\/09671925.pdf?arnumber=9671925","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T22:06:32Z","timestamp":1674425192000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9671925\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,15]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/bigdata52589.2021.9671925","relation":{},"subject":[],"published":{"date-parts":[[2021,12,15]]}}}