{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T18:48:45Z","timestamp":1784054925410,"version":"3.55.0"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T00:00:00Z","timestamp":1658102400000},"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":[[2022,7,18]]},"DOI":"10.1109\/ijcnn55064.2022.9892376","type":"proceedings-article","created":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T15:56:04Z","timestamp":1664553364000},"page":"01-08","source":"Crossref","is-referenced-by-count":48,"title":["AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks"],"prefix":"10.1109","author":[{"given":"Yimin","family":"Yang","sequence":"first","affiliation":[{"name":"Maastricht University,Department of Data Science and Knowledge Engineering,Maastricht,Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siamak","family":"Mehrkanoon","sequence":"additional","affiliation":[{"name":"Maastricht University,Department of Data Science and Knowledge Engineering,Maastricht,Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","article-title":"Deepvit: Towards deeper vision transformer","author":"zhou","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref32","article-title":"Towards learning convolutions from scratch","author":"neyshabur","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref31","article-title":"Vision transformer for small-size datasets","author":"lee","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref30","first-page":"1174","article-title":"Stochastic video generation with a learned prior","author":"denton","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.3389\/fncom.2020.00006"},{"key":"ref34","first-page":"1050","article-title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning","author":"gal","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI47803.2020.9308323"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.14428\/esann\/2021.ES2021-25"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI50451.2021.9660040"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI50451.2021.9659860"},{"key":"ref14","article-title":"TENT: Tensorized Encoder Transformer for temperature forecasting","author":"bilgin","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref15","article-title":"Deep coastal sea elements forecasting using U - Net based models","author":"fernandez","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref16","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IPTA50016.2020.9286606"},{"key":"ref19","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"0","journal-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0230114"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.05.009"},{"key":"ref27","first-page":"802","article-title":"Convolutional lstm network: A machine learning approach for precipitation nowcasting","author":"xingjian","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/nature14956"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2021.08.036"},{"key":"ref29","article-title":"Machine learning for precipitation nowcasting from radar images","author":"agrawal","year":"2019","journal-title":"ArXiv Preprint"},{"key":"ref5","first-page":"178","volume":"145","author":"trebing","year":"2021","journal-title":"SmaAt-UN et Precipitation nowcasting using a small attentionunet architecture"},{"key":"ref8","author":"goodfellow","year":"2016","journal-title":"Deep Learning"},{"key":"ref7","author":"yegnanarayana","year":"2009","journal-title":"Artificial Neural Networks"},{"key":"ref2","author":"de luca","year":"2013","journal-title":"Rainfall nowcasting models for early warning systems wong tsw ed"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1029\/2018GL080704"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0434(1999)014<0338:PFUANN>2.0.CO;2"},{"key":"ref20","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref22","article-title":"Investigating the limitations of transformers with simple arithmetic tasks","author":"nogueira","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref21","article-title":"An image is worth 16&#x00D7;16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref24","first-page":"3","article-title":"Cbam: Convolutional block attention module","author":"woo","year":"0","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref23","article-title":"Transunet: Transformers make strong encoders for medical image segmentation","author":"chen","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"}],"event":{"name":"2022 International Joint Conference on Neural Networks (IJCNN)","location":"Padua, Italy","start":{"date-parts":[[2022,7,18]]},"end":{"date-parts":[[2022,7,23]]}},"container-title":["2022 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9891857\/9889787\/09892376.pdf?arnumber=9892376","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T18:57:04Z","timestamp":1667501824000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9892376\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,18]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/ijcnn55064.2022.9892376","relation":{},"subject":[],"published":{"date-parts":[[2022,7,18]]}}}