{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T17:16:19Z","timestamp":1783790179814,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100004705","name":"King Mongkut's University of Technology Thonburi","doi-asserted-by":"publisher","award":["New Staff Research Grant 2025-2026 (7601.24\/1924)"],"award-info":[{"award-number":["New Staff Research Grant 2025-2026 (7601.24\/1924)"]}],"id":[{"id":"10.13039\/501100004705","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,14]]},"DOI":"10.1145\/3787279.3787308","type":"proceedings-article","created":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T07:38:47Z","timestamp":1777102727000},"page":"179-185","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["TempFuseNet: Temporal Coordination and Progressive Attention-Guided Decoding for Bitemporal Change Detection in Remote Sensing Imagery"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6020-1903","authenticated-orcid":false,"given":"Naveed","family":"Sultan","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, King Mongkuts University of Technology Thonburi, Thung Khru, Bangkok, Thailand,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0869-089X","authenticated-orcid":false,"given":"Santitham","family":"Prom-on","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, King Mongkuts University of Technology Thonburi, Thung Khru, Bangkok, Thailand,"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,25]]},"reference":[{"key":"e_1_3_3_1_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10708-020-10359-1"},{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1134\/S1995425522060154"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2025.104442"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2013.03.006"},{"key":"e_1_3_3_1_5_2","first-page":"229","volume-title":"Exploration of pixel\u2010based and object\u2010based change detection techniques by analyzing ALOS PALSAR and LANDSAT Data,\" Smart and sustainable intelligent systems","author":"Shakya A. K.","year":"2021","unstructured":"A. K. Shakya, A. Ramola, and A. Vidyarthi, \"Exploration of pixel\u2010based and object\u2010based change detection techniques by analyzing ALOS PALSAR and LANDSAT Data,\" Smart and sustainable intelligent systems, pp. 229-244, 2021."},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2021.3119856"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs15143517"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.06.003"},{"key":"e_1_3_3_1_9_2","first-page":"1","article-title":"SNUNet-CD: A densely connected Siamese network for change detection of VHR images","volume":"19","author":"Fang S.","year":"2021","unstructured":"S. Fang, K. Li, J. Shao, and Z. Li, \"SNUNet-CD: A densely connected Siamese network for change detection of VHR images,\" IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2021.","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"key":"e_1_3_3_1_10_2","first-page":"1","volume-title":"MCTNet: A multi-scale CNN-transformer network for change detection in optical remote sensing images,\" in 2023 26th International Conference on Information Fusion (FUSION)","author":"Li W.","year":"2023","unstructured":"W. Li, L. Xue, X. Wang, and G. Li, \"MCTNet: A multi-scale CNN-transformer network for change detection in optical remote sensing images,\" in 2023 26th International Conference on Information Fusion (FUSION), 2023: IEEE, pp. 1-5."},{"key":"e_1_3_3_1_11_2","first-page":"2873","volume-title":"Change detection for high-resolution remote sensing imagery using object-oriented change vector analysis method,\" in 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","author":"Li L.","year":"2016","unstructured":"L. Li, X. Li, Y. Zhang, L. Wang, and G. Ying, \"Change detection for high-resolution remote sensing imagery using object-oriented change vector analysis method,\" in 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016: IEEE, pp. 2873-2876."},{"key":"e_1_3_3_1_12_2","volume-title":"a case study on Pisa Province in Italy,\" International journal of remote sensing","author":"Peiman R.","unstructured":"R. Peiman, \"Pre-classification and post-classification change-detection techniques to monitor land-cover and land-use change using multi-temporal Landsat imagery: a case study on Pisa Province in Italy,\" International journal of remote sensing, vol. 32, no. 15, pp. 4365-4381, 2011."},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2019.111235"},{"key":"e_1_3_3_1_14_2","first-page":"247","article-title":"Building extraction from satellite images using mask R-CNN with building boundary regularization","author":"Zhao K.","year":"2018","unstructured":"K. Zhao, J. Kang, J. Jung, and G. Sohn, \"Building extraction from satellite images using mask R-CNN with building boundary regularization,\" in Proceedings of the IEEE conference on computer vision and pattern recognition workshops, 2018, pp. 247-251.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition workshops"},{"key":"e_1_3_3_1_15_2","first-page":"214","volume-title":"Detecting urban changes with recurrent neural networks from multitemporal Sentinel-2 data,\" in IGARSS 2019-2019 IEEE international geoscience and remote sensing symposium","author":"Papadomanolaki M.","year":"2019","unstructured":"M. Papadomanolaki, S. Verma, M. Vakalopoulou, S. Gupta, and K. Karantzalos, \"Detecting urban changes with recurrent neural networks from multitemporal Sentinel-2 data,\" in IGARSS 2019-2019 IEEE international geoscience and remote sensing symposium, 2019: IEEE, pp. 214-217."},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-archives-XLII-2-419-2018"},{"key":"e_1_3_3_1_17_2","first-page":"1","article-title":"Super-resolution-based change detection network with stacked attention module for images with different resolutions","volume":"60","author":"Liu M.","year":"2021","unstructured":"M. Liu, Q. Shi, A. Marinoni, D. He, X. Liu, and L. Zhang, \"Super-resolution-based change detection network with stacked attention module for images with different resolutions,\" IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-18, 2021.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs12101662"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3034752"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3226418"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2023.3333959"},{"key":"e_1_3_3_1_22_2","first-page":"1","volume-title":"A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection,\" IEEE transactions on geoscience and remote sensing","author":"Shi Q.","year":"2021","unstructured":"Q. Shi, M. Liu, S. Li, X. Liu, F. Wang, and L. Zhang, \"A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection,\" IEEE transactions on geoscience and remote sensing, vol. 60, pp. 1-16, 2021."},{"key":"e_1_3_3_1_23_2","first-page":"1","article-title":"Change detection on remote sensing images using dual-branch multilevel intertemporal network","volume":"61","author":"Feng Y.","year":"2023","unstructured":"Y. Feng, J. Jiang, H. Xu, and J. Zheng, \"Change detection on remote sensing images using dual-branch multilevel intertemporal network,\" IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-15, 2023.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"e_1_3_3_1_24_2","first-page":"1","article-title":"A densely attentive refinement network for change detection based on very-high-resolution bitemporal remote sensing images","volume":"60","author":"Li Z.","year":"2022","unstructured":"Z. Li, C. Yan, Y. Sun, and Q. Xin, \"A densely attentive refinement network for change detection based on very-high-resolution bitemporal remote sensing images,\" IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-18, 2022.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs13132450"},{"key":"e_1_3_3_1_26_2","first-page":"4063","volume-title":"Fully convolutional siamese networks for change detection,\" in 2018 25th IEEE international conference on image processing (ICIP)","author":"Daudt R. C.","year":"2018","unstructured":"R. C. Daudt, B. Le Saux, and A. Boulch, \"Fully convolutional siamese networks for change detection,\" in 2018 25th IEEE international conference on image processing (ICIP), 2018: IEEE, pp. 4063-4067."},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2021.3131993","article-title":"Deep multiscale Siamese network with parallel convolutional structure and self-attention for change detection","volume":"60","author":"Guo Q.","year":"2021","unstructured":"Q. Guo, J. Zhang, S. Zhu, C. Zhong, and Y. Zhang, \"Deep multiscale Siamese network with parallel convolutional structure and self-attention for change detection,\" IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-12, 2021.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"e_1_3_3_1_28_2","first-page":"207","volume-title":"A transformer-based siamese network for change detection,\" in IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium","author":"Bandara W. G. C.","year":"2022","unstructured":"W. G. C. Bandara and V. M. Patel, \"A transformer-based siamese network for change detection,\" in IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium, 2022: IEEE, pp. 207-210."},{"key":"e_1_3_3_1_29_2","first-page":"1","article-title":"An empirical study of remote sensing pretraining","volume":"61","author":"Wang D.","year":"2022","unstructured":"D. Wang, J. Zhang, B. Du, G.-S. Xia, and D. Tao, \"An empirical study of remote sensing pretraining,\" IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-20, 2022.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"e_1_3_3_1_30_2","volume-title":"LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism,\" arXiv preprint arXiv:2410.11580","author":"Liu W.","year":"2024","unstructured":"W. Liu, J. Li, H. Wang, R. Tan, Y. Fu, and Q. Tian, \"LCD-Net: A Lightweight Remote Sensing Change Detection Network Combining Feature Fusion and Gating Mechanism,\" arXiv preprint arXiv:2410.11580, 2024"}],"event":{"name":"ICAAI 2025: 2025 9th International Conference on Advances in Artificial Intelligence","location":"Manchester United Kingdom","acronym":"ICAAI 2025"},"container-title":["Proceedings of the 2025 9th International Conference on Advances in Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3787279.3787308","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T08:23:57Z","timestamp":1777105437000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3787279.3787308"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,14]]},"references-count":30,"alternative-id":["10.1145\/3787279.3787308","10.1145\/3787279"],"URL":"https:\/\/doi.org\/10.1145\/3787279.3787308","relation":{},"subject":[],"published":{"date-parts":[[2025,11,14]]},"assertion":[{"value":"2026-04-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}