{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:39:30Z","timestamp":1757619570551,"version":"3.44.0"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819698684"},{"type":"electronic","value":"9789819698691"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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\/978-981-96-9869-1_37","type":"book-chapter","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T13:43:19Z","timestamp":1753364599000},"page":"437-449","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GASNet: Geometric Robust Adaptive Spatial-Enhanced Network for Building Extraction"],"prefix":"10.1007","author":[{"given":"Bei","family":"Wu","sequence":"first","affiliation":[]},{"given":"Xiangxu","family":"Meng","sequence":"additional","affiliation":[]},{"given":"Heng","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7514-4517","authenticated-orcid":false,"given":"Rahul","family":"Yadav","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9058-852X","authenticated-orcid":false,"given":"Geoff","family":"Nitschke","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0998-5435","authenticated-orcid":false,"given":"Wei","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,7,25]]},"reference":[{"key":"37_CR1","doi-asserted-by":"crossref","unstructured":"Li, P., Liu, G., Tan, L.: Self-supervised vision-language pretraining for medial visual question answering. In: IEEE 20th International Symposium on Biomedical Imaging (ISBI), pp. 1\u20135 (2023)","DOI":"10.1109\/ISBI53787.2023.10230743"},{"key":"37_CR2","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.isprsjprs.2015.03.011","volume":"105","author":"S Du","year":"2015","unstructured":"Du, S., Zhang, F., Zhang, X.: Semantic classification of urban buildings combining VHR image and GIS data: an improved random forest approach. ISPRS J. Photogramm. Remote Sens. 105, 107\u2013119 (2015)","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"37_CR3","doi-asserted-by":"crossref","unstructured":"Li, P., Liu, G., He, J.: Masked vision and language pre-training with unimodal and multimodal contrastive losses for medical visual question answering. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 374\u2013383. Springer, Cham (2023)","DOI":"10.1007\/978-3-031-43907-0_36"},{"key":"37_CR4","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"issue":"6","key":"37_CR5","doi-asserted-by":"publisher","first-page":"1050","DOI":"10.3390\/rs12061050","volume":"12","author":"Z Shao","year":"2020","unstructured":"Shao, Z., Tang, P., Wang, Z., Saleem, N., Yam, S., Sommai, C.: BRRNet: a fully convolutional neural network for automatic building extraction from high-resolution remote sensing images. Remote Sens. 12(6), 1050 (2020)","journal-title":"Remote Sens."},{"issue":"1","key":"37_CR6","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1109\/TGRS.2018.2858817","volume":"57","author":"S Ji","year":"2018","unstructured":"Ji, S., Wei, S., Lu, M.: Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set. IEEE Trans. Geosci. Remote Sens. 57(1), 574\u2013586 (2018)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"37_CR7","doi-asserted-by":"crossref","unstructured":"Zheng, W., Yang, J., Chen, J.: Cross-temporal knowledge injection with color distribution normalization for remote sensing change detection. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. (2025)","DOI":"10.1109\/JSTARS.2025.3534583"},{"issue":"3","key":"37_CR8","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1109\/TNNLS.2020.3041646","volume":"33","author":"H Zhang","year":"2020","unstructured":"Zhang, H., Liao, Y., Yang, H., Yang, G., Zhang, L.: A local\u2013global dual-stream network for building extraction from very-high-resolution remote sensing images. IEEE Trans. Neural Netw. Learn. Syst. 33(3), 1269\u20131283 (2020)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"3","key":"37_CR9","doi-asserted-by":"publisher","first-page":"2178","DOI":"10.1109\/TGRS.2019.2954461","volume":"58","author":"S Wei","year":"2019","unstructured":"Wei, S., Ji, S., Lu, M.: Toward automatic building footprint delineation from aerial images using CNN and regularization. IEEE Trans. Geosci. Remote Sens. 58(3), 2178\u20132189 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"37_CR10","first-page":"1","volume":"60","author":"R Li","year":"2021","unstructured":"Li, R., et al.: Multiattention network for semantic segmentation of fine-resolution remote sensing images. IEEE Trans. Geosci. Remote Sens. 60, 1\u201313 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"37_CR11","first-page":"1","volume":"19","author":"L Wang","year":"2022","unstructured":"Wang, L., Li, R., Duan, C., Zhang, C., Meng, X., Fang, S.: A novel transformer based semantic segmentation scheme for fine-resolution remote sensing images. IEEE Geosci. Remote Sens. Lett. 19, 1\u20135 (2022)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"37_CR12","doi-asserted-by":"crossref","unstructured":"Cao, H., et al.: Swin-UNet: UNet-like pure transformer for medical image segmentation. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 205\u2013218 (2022)","DOI":"10.1007\/978-3-031-25066-8_9"},{"key":"37_CR13","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"issue":"4","key":"37_CR14","doi-asserted-by":"publisher","first-page":"692","DOI":"10.3390\/rs13040692","volume":"13","author":"Y Jin","year":"2021","unstructured":"Jin, Y., Xu, W., Zhang, C., Luo, X., Jia, H.: Boundary-aware refined network for automatic building extraction in very high-resolution urban aerial images. Remote Sens. 13(4), 692 (2021)","journal-title":"Remote Sens."},{"key":"37_CR15","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., Kweon, I.S.: CBAM: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"37_CR16","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in neural information processing systems, vol. 30 (2017)"},{"key":"37_CR17","first-page":"1","volume":"60","author":"L Wang","year":"2022","unstructured":"Wang, L., Fang, S., Meng, X., Li, R.: Building extraction with vision transformer. IEEE Trans. Geosci. Remote Sens. 60, 1\u201311 (2022)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"37_CR18","unstructured":"Katharopoulos, A., Vyas, A., Pappas, N., Fleuret, F.: Transformers are RNNs: fast autoregressive transformers with linear attention. In: International Conference on Machine Learning, pp. 5156\u20135165 (2020)"},{"key":"37_CR19","first-page":"8291","volume":"35","author":"K Han","year":"2022","unstructured":"Han, K., Wang, Y., Guo, J., Tang, Y., Wu, E.: Vision GNN: an image is worth graph of nodes. Adv. Neural. Inf. Process. Syst. 35, 8291\u20138303 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"37_CR20","doi-asserted-by":"crossref","unstructured":"Han, D., et al.: Agent attention: on the integration of softmax and linear attention. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 124\u2013140 (2024)","DOI":"10.1007\/978-3-031-72973-7_8"},{"key":"37_CR21","doi-asserted-by":"crossref","unstructured":"Maggiori, E., Tarabalka, Y., Charpiat, G., Alliez, P.: Can semantic labeling methods generalize to any city? The Inria aerial image labeling benchmark. In: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 3226\u20133229 (2017)","DOI":"10.1109\/IGARSS.2017.8127684"},{"key":"37_CR22","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.isprsjprs.2024.01.022","volume":"209","author":"Y Li","year":"2024","unstructured":"Li, Y., Hong, D., Li, C., Yao, J., Chanussot, J.: HD-Net: high-resolution decoupled network for building footprint extraction via deeply supervised body and boundary decomposition. ISPRS J. Photogramm. Remote Sens. 209, 51\u201365 (2024)","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"37_CR23","first-page":"1","volume":"62","author":"Q Zeng","year":"2024","unstructured":"Zeng, Q., Zhou, J., Tao, J., Chen, L., Niu, X., Zhang, Y.: Multiscale global context network for semantic segmentation of high-resolution remote sensing images. IEEE Trans. Geosci. Remote Sens. 62, 1\u201313 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"37_CR24","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1016\/j.isprsjprs.2022.06.008","volume":"190","author":"L Wang","year":"2022","unstructured":"Wang, L., et al.: UNetFormer: a UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery. ISPRS J. Photogramm. Remote Sens. 190, 196\u2013214 (2022)","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"37_CR25","doi-asserted-by":"crossref","unstructured":"Yang, M., Zhao, L., Ye, L., Jia, W., Jiang, H., Yang, Z.: EGAFNet: an edge guidance and scale-aware adaptive fusion network for building extraction from remote sensing images. IEEE Trans. Geosci. Remote Sens. (2025)","DOI":"10.1109\/TGRS.2024.3524547"},{"key":"37_CR26","first-page":"5608513","volume":"62","author":"J Li","year":"2024","unstructured":"Li, J., He, W., Cao, W., Zhang, L., Zhang, H.: UANet: an uncertainty-aware network for building extraction from remote sensing images. IEEE Trans. Geosci. Remote Sens. 62, 5608513 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9869-1_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T21:58:20Z","timestamp":1757282300000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9869-1_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698684","9789819698691"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9869-1_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"25 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}