{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T16:08:49Z","timestamp":1774454929075,"version":"3.50.1"},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2018,7,1]],"date-time":"2018-07-01T00:00:00Z","timestamp":1530403200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2018,7,1]],"date-time":"2018-07-01T00:00:00Z","timestamp":1530403200000},"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":[[2018,7]]},"DOI":"10.1109\/ijcnn.2018.8489234","type":"proceedings-article","created":{"date-parts":[[2018,10,19]],"date-time":"2018-10-19T18:25:09Z","timestamp":1539973509000},"page":"1-8","source":"Crossref","is-referenced-by-count":5,"title":["ST-DRN: Deep Residual Networks for Spatio-Temporal Metro Stations Crowd Flows Forecast"],"prefix":"10.1109","author":[{"given":"Yang","family":"Ning","sequence":"first","affiliation":[{"name":"University of Science and Technology of China The Comprehend Company, Suzhou, Jiangsu Province, China"}]},{"given":"Yang","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China The Comprehend Company, Suzhou, Jiangsu Province, China"}]},{"given":"Jinyang","family":"Li","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China The Comprehend Company, Suzhou, Jiangsu Province, China"}]},{"given":"Qi","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China The Comprehend Company, Suzhou, Jiangsu Province, China"}]},{"given":"Disheng","family":"Yang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China The Comprehend Company, Suzhou, Jiangsu Province, China"}]},{"given":"Wei","family":"Zheng","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China The Comprehend Company, Suzhou, Jiangsu Province, China"}]},{"given":"Hengchang","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China The Comprehend Company, Suzhou, Jiangsu Province, China"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref11","first-page":"630","article-title":"Identity mappings in deep residual networks","author":"he","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref13","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref14","article-title":"Deep multi-scale video prediction beyond mean square error","author":"mathieu","year":"2015","journal-title":"arXiv preprint arXiv l511 05440"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2007.4408909"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2015.2465959"},{"key":"ref17","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv preprint arXiv 1412 6980"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)0733-947X(2003)129:6(664)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)0733-947X(1999)125:6(515)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2015.7363838"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/S0968-090X(97)82903-8"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2006.869623"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2737095.2737121"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref7","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2030112.2030152"},{"key":"ref1","first-page":"653","article-title":"Traffic flow prediction for road transportation networks with limited traffic data","volume":"16","author":"abadi","year":"2015","journal-title":"Traffic flow prediction for road transportation networks with limited traffic data"},{"key":"ref9","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","author":"sutskever","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2996913.2997016"}],"event":{"name":"2018 International Joint Conference on Neural Networks (IJCNN)","location":"Rio de Janeiro, Brazil","start":{"date-parts":[[2018,7,8]]},"end":{"date-parts":[[2018,7,13]]}},"container-title":["2018 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8465565\/8488986\/08489234.pdf?arnumber=8489234","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,4]],"date-time":"2025-08-04T18:38:03Z","timestamp":1754332683000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8489234\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2018.8489234","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}