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Sevd: Synthetic event-based vision dataset for ego and fixed traffic perception. arXiv preprint arXiv: 2404.10540."},{"key":"10.1016\/j.eswa.2026.132611_bib0003","series-title":"Proceedings of the computer vision and pattern recognition conference","first-page":"9392","article-title":"Divprune: Diversity-based visual token pruning for large multimodal models","author":"Alvar","year":"2025"},{"key":"10.1016\/j.eswa.2026.132611_bib0004","series-title":"2016\u202fIEEE International conference on image processing (ICIP)","first-page":"3464","article-title":"Simple online and realtime tracking","author":"Bewley","year":"2016"},{"key":"10.1016\/j.eswa.2026.132611_bib0005","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"782","article-title":"Transformer interpretability beyond attention visualization","author":"Chefer","year":"2021"},{"key":"10.1016\/j.eswa.2026.132611_bib0006","series-title":"2022 International joint conference on neural networks (IJCNN)","first-page":"1","article-title":"Object detection with spiking neural networks on automotive event data","author":"Cordone","year":"2022"},{"key":"10.1016\/j.eswa.2026.132611_bib0007","unstructured":"De Tournemire, P., Nitti, D., Perot, E., Migliore, D., & Sironi, A. (2020). A large scale event-based detection dataset for automotive. arXiv preprint arXiv: 2001.08499."},{"key":"10.1016\/j.eswa.2026.132611_bib0008","series-title":"Proceedings of the computer vision and pattern recognition conference","first-page":"23080","article-title":"Qmambabsr: Burst image super-resolution with query state space model","author":"Di","year":"2025"},{"key":"10.1016\/j.eswa.2026.132611_bib0009","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/TMM.2023.3260638","article-title":"E-MLB: Multilevel benchmark for event-based camera denoising","volume":"26","author":"Ding","year":"2023","journal-title":"IEEE Transactions on Multimedia"},{"key":"10.1016\/j.eswa.2026.132611_bib0010","unstructured":"Dong, W., Zhu, H., Lin, S., Luo, X., Shen, Y., Liu, X., Zhang, J., Guo, G., & Zhang, B. (2024). 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(2021). 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(2023). 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(2025). Training-free token reduction for vision mamba. arXiv preprint arXiv: 2507.14042."},{"key":"10.1016\/j.eswa.2026.132611_bib0036","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"5419","article-title":"Event-based vision meets deep learning on steering prediction for self-driving cars","author":"Maqueda","year":"2018"},{"key":"10.1016\/j.eswa.2026.132611_bib0037","series-title":"2016\u202fIEEE International conference on image processing (ICIP)","first-page":"1624","article-title":"Performance improvement of deep learning based gesture recognition using spatiotemporal demosaicing technique","author":"Park","year":"2016"},{"key":"10.1016\/j.eswa.2026.132611_bib0038","doi-asserted-by":"crossref","unstructured":"Patro, B. N., & Agneeswaran, V. S. (2024). 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(2015). Convolutional LSTM network: A machine learning approach for precipitation nowcasting. Advances in Neural Information Processing Systems, Curran Associates, Inc. 28. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2015\/file\/07563a3fe3bbe7e3ba84431ad9d055af-Paper.pdf."},{"key":"10.1016\/j.eswa.2026.132611_bib0047","doi-asserted-by":"crossref","unstructured":"Shi, Y., Dong, M., & Xu, C. (2024). 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Dynamic graph induced contour-aware heat conduction network for event-based object detection. arXiv preprint arXiv: 2505.12908."},{"key":"10.1016\/j.eswa.2026.132611_bib0055","series-title":"Proceedings of the computer vision and pattern recognition conference","first-page":"29321","article-title":"Object detection using event camera: A moe heat conduction based detector and a new benchmark dataset","author":"Wang","year":"2025"},{"key":"10.1016\/j.eswa.2026.132611_bib0056","series-title":"Proceedings of the computer vision and pattern recognition conference","first-page":"9707","article-title":"Building vision models upon heat conduction","author":"Wang","year":"2025"},{"key":"10.1016\/j.eswa.2026.132611_bib0057","series-title":"European conference on computer vision","first-page":"310","article-title":"Eas-snn: End-to-end adaptive sampling and representation for event-based detection with recurrent spiking neural networks","author":"Wang","year":"2024"},{"key":"10.1016\/j.eswa.2026.132611_bib0058","series-title":"Proceedings of the european conference on computer vision (ECCV)","first-page":"3","article-title":"Cbam: Convolutional block attention module","author":"Woo","year":"2018"},{"key":"10.1016\/j.eswa.2026.132611_bib0059","unstructured":"Wu, B., Xu, C., Dai, X., Wan, A., Zhang, P., Yan, Z., Tomizuka, M., Gonzalez, J., Keutzer, K., & Vajda, P. 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A survey on vision mamba: Models, applications and challenges. arXiv preprint arXiv: 2404.18861."},{"issue":"5","key":"10.1016\/j.eswa.2026.132611_bib0063","doi-asserted-by":"crossref","first-page":"2200","DOI":"10.1109\/TIP.2018.2883741","article-title":"Two-stream convolutional networks for blind image quality assessment","volume":"28","author":"Yan","year":"2018","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.eswa.2026.132611_bib0064","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"9229","article-title":"Smamba: Sparse mamba for event-based object detection","volume":"vol. 39","author":"Yang","year":"2025"},{"key":"10.1016\/j.eswa.2026.132611_bib0065","unstructured":"Zhan, Z., Wu, Y., Kong, Z., Yang, C., Gong, Y., Shen, X., Lin, X., Zhao, P., & Wang, Y. (2024). Rethinking token reduction for state space models. arXiv preprint arXiv: 2410.14725."},{"issue":"4","key":"10.1016\/j.eswa.2026.132611_bib0066","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/j.inffus.2012.05.002","article-title":"Multi-metric learning for multi-sensor fusion based classification","volume":"14","author":"Zhang","year":"2013","journal-title":"Information Fusion"},{"key":"10.1016\/j.eswa.2026.132611_bib0067","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"989","article-title":"Unsupervised event-based learning of optical flow, depth, and egomotion","author":"Zhu","year":"2019"},{"key":"10.1016\/j.eswa.2026.132611_bib0068","unstructured":"Zhu, L., Liao, B., Zhang, Q., Wang, X., Liu, W., & Wang, X. (2024). Vision mamba: Efficient visual representation learning with bidirectional state space model. arXiv preprint arXiv: 2401.09417."},{"key":"10.1016\/j.eswa.2026.132611_bib0069","series-title":"The thirty-ninth annual conference on neural information processing systems","article-title":"Rethinking scale-aware temporal encoding for event-based object detection","author":"Zhu","year":"2025"},{"key":"10.1016\/j.eswa.2026.132611_bib0070","series-title":"Acm multimedia 2024","article-title":"Wave-mamba: Wavelet state space model for ultra-high-definition low-light image enhancement","author":"Zou","year":"2024"},{"key":"10.1016\/j.eswa.2026.132611_bib0071","series-title":"Proceedings of the IEEE\/CVF international conference on computer vision (ICCV)","first-page":"12846","article-title":"From chaos comes order: Ordering event representations for object recognition and detection","author":"Zubi\u0107","year":"2023"},{"key":"10.1016\/j.eswa.2026.132611_bib0072","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"5819","article-title":"State space models for event cameras","author":"Zubic","year":"2024"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426015241?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426015241?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T10:43:50Z","timestamp":1783075430000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426015241"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":72,"alternative-id":["S0957417426015241"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132611","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"SCSMamba: Spatial-channel sparse Mamba for event-based object detection","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132611","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"132611"}}