{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T12:41:24Z","timestamp":1766061684288,"version":"3.48.0"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"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","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,19]]},"DOI":"10.1109\/iros60139.2025.11247390","type":"proceedings-article","created":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T18:54:45Z","timestamp":1764269685000},"page":"11607-11613","source":"Crossref","is-referenced-by-count":0,"title":["3DWSNet: A Novel 3D Wavelet Spiking Neural Network for Event-based Action Recognition"],"prefix":"10.1109","author":[{"given":"Junkang","family":"Fang","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications,School of Intelligent Engineering and Automation,Beijing,China,100876"}]},{"given":"Yonghao","family":"Dang","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications,School of Intelligent Engineering and Automation,Beijing,China,100876"}]},{"given":"Wending","family":"Zhao","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications,School of Intelligent Engineering and Automation,Beijing,China,100876"}]},{"given":"Bo","family":"Yu","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications,School of Intelligent Engineering and Automation,Beijing,China,100876"}]},{"given":"Zehao","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications,School of Intelligent Engineering and Automation,Beijing,China,100876"}]},{"given":"Jianqin","family":"Yin","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications,School of Intelligent Engineering and Automation,Beijing,China,100876"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/240"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS58592.2024.10802384"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2019.00095"},{"key":"ref4","first-page":"21 056","article-title":"Deep residual learning in spiking neural networks","volume":"34","author":"Fang","year":"2021","journal-title":"in Neural Information Processing Systems"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.patter.2022.100522"},{"article-title":"Spikformer: When spiking neural network meets transformer","volume-title":"International Conference on Learning Representations","author":"Zhou","key":"ref6"},{"key":"ref7","article-title":"Spike-driven transformer","author":"Yao","year":"2023","journal-title":"Neural Information Processing Systems"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00536"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73116-7_2"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2019.2931595"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1162\/neco_a_01367"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2015.7280696"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/321"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01357"},{"key":"ref15","first-page":"6316","article-title":"A free lunch from ann: Towards efficient, accurate spiking neural networks calibration","volume-title":"International Conference on Machine Learning","author":"Li"},{"article-title":"Optimal annsnn conversion for high-accuracy and ultra-low-latency spiking neural networks","year":"2023","author":"Bu","key":"ref16"},{"article-title":"Bridging the gap between anns and snns by calibrating offset spikes","year":"2023","author":"Hao","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.00119"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3119238"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17320"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"article-title":"Spikingformer: Spike-driven residual learning for transformer-based spiking neural network","year":"2023","author":"Zhou","key":"ref22"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00266"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.111094"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01006"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.10.056"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2024\/347"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i10.29066"},{"article-title":"TAB: temporal accumulated batch normalization in spiking neural networks","volume-title":"International Conference on Learning Representations","author":"Jiang","key":"ref29"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3377717"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2018.00331"},{"key":"ref32","first-page":"23 426","article-title":"Differentiable spike: Rethinking gradient-descent for training spiking neural networks","author":"Li","year":"2021","journal-title":"Neural Information Processing Systems"},{"key":"ref33","article-title":"Advancing training efficiency of deep spiking neural networks through rate-based back-propagation","author":"Yu","year":"2024","journal-title":"Neural Information Processing Systems"},{"key":"ref34","article-title":"Qkformer: Hierarchical spiking transformer using Q-K attention","author":"Zhou","year":"2024","journal-title":"Neural Information Processing Systems"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.52202\/079017-4092"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2017.00309"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"article-title":"Temporal efficient training of spiking neural network via gradient re-weighting","volume-title":"International Conference on Learning Representations","author":"Deng","key":"ref38"}],"event":{"name":"2025 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","start":{"date-parts":[[2025,10,19]]},"location":"Hangzhou, China","end":{"date-parts":[[2025,10,25]]}},"container-title":["2025 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11245651\/11245652\/11247390.pdf?arnumber=11247390","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T12:38:21Z","timestamp":1766061501000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11247390\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/iros60139.2025.11247390","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}