{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T10:38:19Z","timestamp":1760524699145,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031783111"},{"type":"electronic","value":"9783031783128"}],"license":[{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,4]],"date-time":"2024-12-04T00:00:00Z","timestamp":1733270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-78312-8_15","type":"book-chapter","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T12:37:34Z","timestamp":1733229454000},"page":"221-236","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MMSISP: A Satellite Image Sequence Prediction Network with Multi-factor Decoupling and Multi-modal Fusion"],"prefix":"10.1007","author":[{"given":"Fanbin","family":"Mo","sequence":"first","affiliation":[]},{"given":"Yixiang","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Ming","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Xun","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Chuang","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,4]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Dai, K., Li, X., Ma, C., Lu, S., Ye, Y., Xian, D., Tian, L., Qin, D.: Learning spatial-temporal consistency for satellite image sequence prediction. IEEE Transactions on Geoscience and Remote Sensing (2023)","DOI":"10.1109\/TGRS.2023.3303947"},{"key":"15_CR2","first-page":"1","volume":"60","author":"K Dai","year":"2022","unstructured":"Dai, K., Li, X., Ye, Y., Feng, S., Qin, D., Ye, R.: Mstcgan: Multiscale time conditional generative adversarial network for long-term satellite image sequence prediction. IEEE Trans. Geosci. Remote Sens. 60, 1\u201316 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"15_CR3","doi-asserted-by":"crossref","unstructured":"Gao, Z., Tan, C., Wu, L., Li, S.Z.: Simvp: Simpler yet better video prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 3170\u20133180 (2022)","DOI":"10.1109\/CVPR52688.2022.00317"},{"key":"15_CR4","unstructured":"Guen, V.L., Thome, N.: Disentangling physical dynamics from unknown factors for unsupervised video prediction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 11474\u201311484 (2020)"},{"key":"15_CR5","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.rse.2012.11.013","volume":"131","author":"FA Hirpa","year":"2013","unstructured":"Hirpa, F.A., Hopson, T.M., De Groeve, T., Brakenridge, G.R., Gebremichael, M., Restrepo, P.J.: Upstream satellite remote sensing for river discharge forecasting: Application to major rivers in south asia. Remote Sens. Environ. 131, 140\u2013151 (2013)","journal-title":"Remote Sens. Environ."},{"issue":"1\u20133","key":"15_CR6","first-page":"185","volume":"17","author":"BK Horn","year":"1981","unstructured":"Horn, B.K., Schunck, B.G.: Determining optical flow. Artificial intelligence 17(1\u20133), 185\u2013203 (1981)","journal-title":"Determining optical flow. Artificial intelligence"},{"issue":"3","key":"15_CR7","doi-asserted-by":"publisher","first-page":"2212","DOI":"10.1109\/TGRS.2019.2955538","volume":"58","author":"JH Lee","year":"2019","unstructured":"Lee, J.H., Lee, S.S., Kim, H.G., Song, S.K., Kim, S., Ro, Y.M.: Mcsip net: Multichannel satellite image prediction via deep neural network. IEEE Trans. Geosci. Remote Sens. 58(3), 2212\u20132224 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Leinonen, J., Hamann, U., Nerini, D., Germann, U., Franch, G.: Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification. arXiv preprint arXiv:2304.12891 (2023)","DOI":"10.5194\/egusphere-egu23-9531"},{"issue":"7878","key":"15_CR9","doi-asserted-by":"publisher","first-page":"672","DOI":"10.1038\/s41586-021-03854-z","volume":"597","author":"S Ravuri","year":"2021","unstructured":"Ravuri, S., Lenc, K., Willson, M., Kangin, D., Lam, R., Mirowski, P., Fitzsimons, M., Athanassiadou, M., Kashem, S., Madge, S., et al.: Skilful precipitation nowcasting using deep generative models of radar. Nature 597(7878), 672\u2013677 (2021)","journal-title":"Nature"},{"key":"15_CR10","unstructured":"Shi, X., Chen, Z., Wang, H., Yeung, D.Y., Wong, W.K., Woo, W.c.: Convolutional lstm network: A machine learning approach for precipitation nowcasting. Advances in neural information processing systems 28 (2015)"},{"issue":"7","key":"15_CR11","doi-asserted-by":"publisher","first-page":"4155","DOI":"10.1109\/TGRS.2013.2280094","volume":"52","author":"BP Shukla","year":"2013","unstructured":"Shukla, B.P., Kishtawal, C.M., Pal, P.K.: Prediction of satellite image sequence for weather nowcasting using cluster-based spatiotemporal regression. IEEE Trans. Geosci. Remote Sens. 52(7), 4155\u20134160 (2013)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"9","key":"15_CR12","doi-asserted-by":"publisher","first-page":"12373","DOI":"10.1007\/s12652-022-04333-7","volume":"14","author":"Y Son","year":"2023","unstructured":"Son, Y., Zhang, X., Yoon, Y., Cho, J., Choi, S.: Lstm-gan based cloud movement prediction in satellite images for pv forecast. J. Ambient. Intell. Humaniz. Comput. 14(9), 12373\u201312386 (2023)","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Tan, C., Gao, Z., Wu, L., Xu, Y., Xia, J., Li, S., Li, S.Z.: Temporal attention unit: Towards efficient spatiotemporal predictive learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 18770\u201318782 (2023)","DOI":"10.1109\/CVPR52729.2023.01800"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Tang, S., Li, C., Zhang, P., Tang, R.: Swinlstm: Improving spatiotemporal prediction accuracy using swin transformer and lstm. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp. 13470\u201313479 (2023)","DOI":"10.1109\/ICCV51070.2023.01239"},{"issue":"5","key":"15_CR15","doi-asserted-by":"publisher","first-page":"1239","DOI":"10.1007\/s11263-019-01188-y","volume":"128","author":"A Valada","year":"2020","unstructured":"Valada, A., Mohan, R., Burgard, W.: Self-supervised model adaptation for multimodal semantic segmentation. Int. J. Comput. Vision 128(5), 1239\u20131285 (2020)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR16","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30 (2017)"},{"key":"15_CR17","unstructured":"Wang, Y., Gao, Z., Long, M., Wang, J., Philip, S.Y.: Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning. In: International Conference on Machine Learning. pp. 5123\u20135132. PMLR (2018)"},{"key":"15_CR18","unstructured":"Wang, Y., Long, M., Wang, J., Gao, Z., Yu, P.S.: Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms. Advances in neural information processing systems 30 (2017)"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zhang, J., Zhu, H., Long, M., Wang, J., Yu, P.S.: Memory in memory: A predictive neural network for learning higher-order non-stationarity from spatiotemporal dynamics. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp. 9154\u20139162 (2019)","DOI":"10.1109\/CVPR.2019.00937"},{"key":"15_CR20","doi-asserted-by":"crossref","unstructured":"Wu, H., Yao, Z., Wang, J., Long, M.: Motionrnn: A flexible model for video prediction with spacetime-varying motions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp. 15435\u201315444 (2021)","DOI":"10.1109\/CVPR46437.2021.01518"},{"key":"15_CR21","doi-asserted-by":"crossref","unstructured":"Xu, Z., Du, J., Wang, J., Jiang, C., Ren, Y.: Satellite image prediction relying on gan and lstm neural networks. In: ICC 2019-2019 IEEE international conference on communications (ICC). pp.\u00a01\u20136. IEEE (2019)","DOI":"10.1109\/ICC.2019.8761462"},{"issue":"7970","key":"15_CR22","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1038\/s41586-023-06184-4","volume":"619","author":"Y Zhang","year":"2023","unstructured":"Zhang, Y., Long, M., Chen, K., Xing, L., Jin, R., Jordan, M.I., Wang, J.: Skilful nowcasting of extreme precipitation with nowcastnet. Nature 619(7970), 526\u2013532 (2023)","journal-title":"Nature"},{"key":"15_CR23","doi-asserted-by":"crossref","unstructured":"Zhong, Y., Liang, L., Zharkov, I., Neumann, U.: Mmvp: Motion-matrix-based video prediction. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. pp. 4273\u20134283 (2023)","DOI":"10.1109\/ICCV51070.2023.00394"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-78312-8_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T13:05:41Z","timestamp":1733231141000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-78312-8_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,4]]},"ISBN":["9783031783111","9783031783128"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-78312-8_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,12,4]]},"assertion":[{"value":"4 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}