{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T03:52:16Z","timestamp":1774410736186,"version":"3.50.1"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3339152","type":"journal-article","created":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T18:57:03Z","timestamp":1701716223000},"page":"137734-137746","source":"Crossref","is-referenced-by-count":5,"title":["SAU-Net: Monocular Depth Estimation Combining Multi-Scale Features and Attention Mechanisms"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-7865-4271","authenticated-orcid":false,"given":"Wei","family":"Zhao","sequence":"first","affiliation":[{"name":"China College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9203-130X","authenticated-orcid":false,"given":"Yunqing","family":"Song","sequence":"additional","affiliation":[{"name":"China College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5408-3333","authenticated-orcid":false,"given":"Tingting","family":"Wang","sequence":"additional","affiliation":[{"name":"China College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang, China"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Improving online lane graph extraction by object-lane clustering","author":"Can","year":"2023","journal-title":"arXiv:2307.10947"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2022.3142246"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811774"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3064270"},{"key":"ref5","article-title":"Automatic map update using dashcam videos","author":"Zhanabatyrova","year":"2021","journal-title":"arXiv:2109.12131"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/icaccs57279.2023.10112912"},{"key":"ref7","article-title":"Depth map prediction from a single image using a multi-scale deep network","author":"Eigen","year":"2014","journal-title":"arXiv:1406.2283"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2015.7298715"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00037"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_45"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2017.699"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/iccv.2019.00225"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2023.104834"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3244793"},{"key":"ref16","article-title":"GANDiffFace: Controllable generation of synthetic datasets for face recognition with realistic variations","author":"Melzi","year":"2023","journal-title":"arXiv:2305.19962"},{"key":"ref17","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2017","journal-title":"arXiv:1709.01507"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01181"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160476"},{"key":"ref21","article-title":"Vision transformers for mobile applications: A short survey","author":"Alam","year":"2023","journal-title":"arXiv:2305.19365"},{"key":"ref22","article-title":"Towards omni-generalizable neural methods for vehicle routing problems","author":"Zhou","year":"2023","journal-title":"arXiv:2305.19587"},{"key":"ref23","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020","journal-title":"arXiv:2010.11929"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096645"},{"key":"ref25","article-title":"Source-free domain adaptation for RGB-D semantic segmentation with vision transformers","author":"Rizzoli","year":"2023","journal-title":"arXiv:2305.14269"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548446"},{"key":"ref27","article-title":"MaxViT-UNet: Multi-axis attention for medical image segmentation","author":"Rehman Khan","year":"2023","journal-title":"arXiv:2305.08396"},{"key":"ref28","article-title":"STM-UNet: An efficient U-shaped architecture based on Swin transformer and multi-scale MLP for medical image segmentation","author":"Shi","year":"2023","journal-title":"arXiv:2304.12615"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120128"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11030354"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/s22030721"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12061450"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/iccv.2019.00393"},{"issue":"2","key":"ref34","first-page":"217","article-title":"Anti occlusion monocular depth estimation algorithm","volume":"57","author":"Ma","year":"2021","journal-title":"Comput. Eng. Appl."},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/tcsvt.2021.3049869"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/iccv48922.2021.00986"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/iwqos.2018.8624183"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01495"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2015.2505283"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_43"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_30"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2018.00214"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2019.2930258"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr42600.2020.00256"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10339924.pdf?arnumber=10339924","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T01:23:24Z","timestamp":1705022604000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10339924\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3339152","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}