{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T20:58:25Z","timestamp":1787777905155,"version":"build-2784847793"},"publisher-location":"Singapore","reference-count":23,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819567850","type":"print"},{"value":"9789819567867","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-6786-7_20","type":"book-chapter","created":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T18:07:01Z","timestamp":1770919621000},"page":"302-315","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["BARE: Boundary-Aware with\u00a0Resolution Enhancement for\u00a0Tree Crown Delineation"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3084-9419","authenticated-orcid":false,"given":"Attavit","family":"Wilaiwongsakul","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6605-2167","authenticated-orcid":false,"given":"Bin","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3996-5438","authenticated-orcid":false,"given":"Wenfeng","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1223-9230","authenticated-orcid":false,"given":"Bryan","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4971-8729","authenticated-orcid":false,"given":"Fang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,13]]},"reference":[{"key":"20_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolind.2024.112110","volume":"163","author":"R Al-Ruzouq","year":"2024","unstructured":"Al-Ruzouq, R., et al.: Spectral-Spatial transformer-based semantic segmentation for large-scale mapping of individual date palm trees using very high-resolution satellite data. Ecol. Ind. 163, 112110 (2024). https:\/\/doi.org\/10.1016\/j.ecolind.2024.112110","journal-title":"Ecol. Ind."},{"key":"20_CR2","doi-asserted-by":"publisher","unstructured":"Cheng, B., Girshick, R., Doll\u00e1r, P., Berg, A.C., Kirillov, A.: Boundary IoU: Improving object-centric image segmentation evaluation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp. 15334\u201315342. IEEE (2021). https:\/\/doi.org\/10.1109\/cvpr46437.2021.01508","DOI":"10.1109\/cvpr46437.2021.01508"},{"key":"20_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tgrs.2023.3276172","volume":"61","author":"G Deng","year":"2023","unstructured":"Deng, G., Wu, Z., Xu, M., Wang, C., Wang, Z., Lu, Z.: Crisscross-global vision transformers model for very high resolution aerial image semantic segmentation. IEEE Trans. Geosci. Remote Sens. 61, 1\u201319 (2023). https:\/\/doi.org\/10.1109\/tgrs.2023.3276172","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"20_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophoto.2023.100037","volume":"8","author":"S Dersch","year":"2023","unstructured":"Dersch, S., Sch\u00f6ttl, A., Krzystek, P., Heurich, M.: Towards complete tree crown delineation by instance segmentation with Mask R-CNN and DETR using UAV-based multispectral imagery and lidar data. ISPRS Open J. Photogram. Remote Sens. 8, 100037 (2023). https:\/\/doi.org\/10.1016\/j.ophoto.2023.100037","journal-title":"ISPRS Open J. Photogram. Remote Sens."},{"key":"20_CR5","doi-asserted-by":"publisher","unstructured":"Dosovitskiy, A., et\u00a0al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020). https:\/\/doi.org\/10.48550\/arXiv.2010.11929","DOI":"10.48550\/arXiv.2010.11929"},{"issue":"24","key":"20_CR6","doi-asserted-by":"publisher","first-page":"22197","DOI":"10.1007\/s00521-022-07640-4","volume":"34","author":"M Freudenberg","year":"2022","unstructured":"Freudenberg, M., Magdon, P., N\u00f6lke, N.: Individual tree crown delineation in high-resolution remote sensing images based on U-Net. Neural Comput. Appl. 34(24), 22197\u201322207 (2022). https:\/\/doi.org\/10.1007\/s00521-022-07640-4","journal-title":"Neural Comput. Appl."},{"key":"20_CR7","doi-asserted-by":"publisher","unstructured":"Georges\u00a0Gomes, et al.: Urban Trees Mapping Using multi-scale rgb image and deep learning vision transformer-based. SSRN Electr. J. (2022). https:\/\/doi.org\/10.2139\/ssrn.4167085","DOI":"10.2139\/ssrn.4167085"},{"key":"20_CR8","doi-asserted-by":"publisher","unstructured":"Gibril, M.B.A., Shafri, H.Z.M., Al-Ruzouq, R., Shanableh, A., Nahas, F., Al\u00a0Mansoori, S.: Large-scale date palm tree segmentation from multiscale Uav-based and aerial images using deep vision transformers. Drones 7(2), 93 (2023). https:\/\/doi.org\/10.3390\/drones7020093","DOI":"10.3390\/drones7020093"},{"key":"20_CR9","doi-asserted-by":"publisher","unstructured":"Gominski, D., Kariryaa, A., Brandt, M., Igel, C., Li, S., Mugabowindekwe, M., Fensholt, R.: Benchmarking Individual Tree Mapping with Sub-meter Imagery. arXiv.org (2023). https:\/\/doi.org\/10.48550\/arXiv.2311.07981","DOI":"10.48550\/arXiv.2311.07981"},{"key":"20_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tgrs.2023.3302024","volume":"61","author":"Y Liu","year":"2023","unstructured":"Liu, Y., Zhang, Y., Wang, Y., Mei, S.: Rethinking Transformers for Semantic Segmentation of Remote Sensing Images. IEEE Trans. Geosci. Remote Sens. 61, 1\u201315 (2023). https:\/\/doi.org\/10.1109\/tgrs.2023.3302024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"20_CR11","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1080\/01431161.2023.2292550","volume":"45","author":"D Ren","year":"2023","unstructured":"Ren, D., Li, F., Sun, H., Liu, L., Ren, S., Yu, M.: Local-enhanced multi-scale aggregation swin transformer for semantic segmentation of high-resolution remote sensing images. Int. J. Remote Sens. 45(1), 101\u2013120 (2023). https:\/\/doi.org\/10.1080\/01431161.2023.2292550","journal-title":"Int. J. Remote Sens."},{"key":"20_CR12","doi-asserted-by":"publisher","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: Convolutional Networks for Biomedical Image Segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"20_CR13","doi-asserted-by":"publisher","unstructured":"Tao, Y., Wang, Z., Zhao, G.: Shadow-resilient tree crown detection in uav remote sensing images using deep learning. In: 2024 4th International Conference on Computer Science and Blockchain (CCSB). pp. 318\u2013322. IEEE (2024). https:\/\/doi.org\/10.1109\/ccsb63463.2024.10735679","DOI":"10.1109\/ccsb63463.2024.10735679"},{"key":"20_CR14","doi-asserted-by":"publisher","unstructured":"Veitch-Michaelis, J., et al.: Oam-TCD: A globally diverse dataset of high-resolution tree cover maps. arXiv.org (2024). https:\/\/doi.org\/10.48550\/arXiv.2407.11743","DOI":"10.48550\/arXiv.2407.11743"},{"issue":"14","key":"20_CR15","doi-asserted-by":"publisher","first-page":"3607","DOI":"10.3390\/rs15143607","volume":"15","author":"D Wang","year":"2023","unstructured":"Wang, D., Chen, Y., Naz, B., Sun, L., Li, B.: Spatial-aware transformer (SAT): enhancing global modeling in transformer segmentation for remote sensing images. Remote Sens. 15(14), 3607 (2023). https:\/\/doi.org\/10.3390\/rs15143607","journal-title":"Remote Sens."},{"key":"20_CR16","doi-asserted-by":"publisher","unstructured":"Wang, Y., Yang, G., Lu, H.: Domain adaptive tree crown detection using high-resolution remote sensing images. J. Appl. Remote Sens.16(04) (2022). https:\/\/doi.org\/10.1117\/1.jrs.16.044505","DOI":"10.1117\/1.jrs.16.044505"},{"key":"20_CR17","doi-asserted-by":"publisher","unstructured":"Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J.M., Luo, P.: Segformer: simple and efficient design for semantic segmentation with transformers. Adv. Neural Inf. Process. Sys. 34, 12077\u201312090 (2021). https:\/\/doi.org\/10.48550\/arXiv.2105.15203","DOI":"10.48550\/arXiv.2105.15203"},{"issue":"18","key":"20_CR18","doi-asserted-by":"publisher","first-page":"3585","DOI":"10.3390\/rs13183585","volume":"13","author":"Z Xu","year":"2021","unstructured":"Xu, Z., Zhang, W., Zhang, T., Yang, Z., Li, J.: Efficient Transformer for Remote Sensing Image Segmentation. Remote Sen. 13(18), 3585 (2021). https:\/\/doi.org\/10.3390\/rs13183585","journal-title":"Remote Sen."},{"key":"20_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tgrs.2022.3144894","volume":"60","author":"C Zhang","year":"2022","unstructured":"Zhang, C., Jiang, W., Zhang, Y., Wang, W., Zhao, Q., Wang, C.: Transformer and CNN Hybrid Deep Neural Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery. IEEE Trans. Geosci. Remote Sens. 60, 1\u201320 (2022). https:\/\/doi.org\/10.1109\/tgrs.2022.3144894","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"20_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/tgrs.2024.3430081","volume":"62","author":"J Zhang","year":"2024","unstructured":"Zhang, J., Shao, M., Wan, Y., Meng, L., Cao, X., Wang, S.: Boundary-aware spatial and frequency dual-domain transformer for remote sensing urban images segmentation. IEEE Trans. Geosci. Remote Sens. 62, 1\u201318 (2024). https:\/\/doi.org\/10.1109\/tgrs.2024.3430081","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"20_CR21","doi-asserted-by":"publisher","unstructured":"Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.: Pyramid scene parsing network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 2881\u20132890 (2017). https:\/\/doi.org\/10.48550\/arXiv.1612.01105","DOI":"10.48550\/arXiv.1612.01105"},{"key":"20_CR22","doi-asserted-by":"publisher","unstructured":"Zheng, S., et\u00a0al.: Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. pp. 6881\u20136890 (2021). https:\/\/doi.org\/10.48550\/arXiv.2012.15840","DOI":"10.48550\/arXiv.2012.15840"},{"key":"20_CR23","doi-asserted-by":"publisher","first-page":"7040","DOI":"10.1109\/jstars.2024.3378167","volume":"17","author":"F Zhu","year":"2024","unstructured":"Zhu, F., Chen, Z., Li, H., Shi, Q., Liu, X.: Cedanet: individual tree segmentation in dense orchard via context enhancement and density prior. IEEE J. Sel. Appl. Earth Obs. Remote Sens. 17, 7040\u20137051 (2024). https:\/\/doi.org\/10.1109\/jstars.2024.3378167","journal-title":"IEEE J. Sel. Appl. Earth Obs. Remote Sens."}],"container-title":["Communications in Computer and Information Science","Data Science and Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-6786-7_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T18:07:02Z","timestamp":1770919622000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-6786-7_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819567850","9789819567867"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-6786-7_20","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"13 February 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"AusDM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australasian Conference on Data Science and Machine Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brisbane","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","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 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ausdm2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ausdm25.ausdm.org\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}