{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T16:22:09Z","timestamp":1790094129606,"version":"4.0.1"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62203257"],"award-info":[{"award-number":["62203257"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62325405"],"award-info":[{"award-number":["62325405"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62031017"],"award-info":[{"award-number":["62031017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tsinghua University Initiative Scientific Research Program"},{"name":"Tsinghua-Efort Joint Research Center for EAI Computation and Perception"},{"name":"Beijing National Research Center for Information Science"},{"name":"Beijing Innovation Center for Future Chips"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1109\/lra.2025.3548504","type":"journal-article","created":{"date-parts":[[2025,3,5]],"date-time":"2025-03-05T18:57:24Z","timestamp":1741201044000},"page":"4308-4315","source":"Crossref","is-referenced-by-count":3,"title":["Efficient and Hardware-Friendly Online Adaptation for Deep Stereo Depth Estimation on Embedded Robots"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5671-3734","authenticated-orcid":false,"given":"Yuanfan","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3236-4195","authenticated-orcid":false,"given":"Shuaiwen","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinting","family":"Yang","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunfei","family":"Xiang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3831-3845","authenticated-orcid":false,"given":"Jincheng","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0597-4512","authenticated-orcid":false,"given":"Wenbo","family":"Ding","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7683-6937","authenticated-orcid":false,"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6108-5157","authenticated-orcid":false,"given":"Yu","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340897"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abm5954"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2023.3236945"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00567"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00027"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_25"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197031"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794003"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.02.014"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9562012"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3075815"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01906"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.08.045"},{"key":"ref15","first-page":"22941","article-title":"On-device training under 256 KB memory","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lin","year":"2022"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-industry.12"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/MM.2020.2975764"},{"key":"ref18","volume-title":"","year":"2023"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10161258"},{"key":"ref20","first-page":"451","article-title":"Training DNNs with hybrid block floating point","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Drumond","year":"2018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2021.3066400"},{"key":"ref22","first-page":"1","article-title":"Mixed precision training","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Micikevicius","year":"2018"},{"key":"ref23","first-page":"4900","article-title":"Hybrid 8-bit floating point (HFP8) training and inference for deep neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sun","year":"2019"},{"key":"ref24","first-page":"7686","article-title":"Training deep neural networks with 8-bit floating point numbers","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wang","year":"2018"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3032602"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02099"},{"key":"ref27","first-page":"573","article-title":"Stereonet: Guided hierarchical refinement for real-time edge-aware depth prediction","volume-title":"Proc. Eur. Conf. Comput. Vis.","author":"Khamis","year":"2018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00028"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00989"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.699"},{"issue":"59","key":"ref31","doi-asserted-by":"crossref","DOI":"10.1126\/scirobotics.abg5810","article-title":"Learning high-speed flight in the wild","volume":"6","author":"Loquercio","year":"2021","journal-title":"Sci. Robot."},{"key":"ref32","first-page":"1","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Han","year":"2016"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2020.3043870"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA53966.2022.00067"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1201\/9781003162810-13","article-title":"A survey of quantization methods for efficient neural network inference","volume-title":"Low-Power Computer Vision","author":"Gholami","year":"2022"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.438"},{"key":"ref38","volume-title":"","year":"2017"},{"key":"ref39","volume-title":"","year":"2022"},{"key":"ref40","volume-title":"","year":"2023"},{"key":"ref41","volume-title":"","year":"2023"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7083369\/10935293\/10910155.pdf?arnumber=10910155","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T02:54:40Z","timestamp":1743044080000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10910155\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":41,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/lra.2025.3548504","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5]]}}}