{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T19:06:41Z","timestamp":1742929601856,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319715971"},{"type":"electronic","value":"9783319715988"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-71598-8_54","type":"book-chapter","created":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T01:26:32Z","timestamp":1514510792000},"page":"611-620","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Improved Fully Convolutional Network for the Detection of Built-up Areas in High Resolution SAR Images"],"prefix":"10.1007","author":[{"given":"Ding-Li","family":"Gao","sequence":"first","affiliation":[]},{"given":"Rong","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Di-Xiu","family":"Xue","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,12,30]]},"reference":[{"key":"54_CR1","unstructured":"Yang, W., et al.: Supervised land-cover classification of TerraSAR-X imagery over urban areas using extremely randomized clustering forests. In: 2009 Joint Urban Remote Sensing Event (2009). IEEE"},{"key":"54_CR2","doi-asserted-by":"crossref","unstructured":"Li, N., et al.: Labeled co-occurrence matrix for the detection of built-up areas in high-resolution SAR images. In: SPIE Remote Sensing. International Society for Optics and Photonics (2013)","DOI":"10.1117\/12.2029872"},{"key":"54_CR3","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"issue":"3","key":"54_CR4","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis."},{"key":"54_CR5","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). 1, 2, 3, 4, 5, 6, 7, 8"},{"key":"54_CR6","unstructured":"Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. arXiv preprint arXiv:1606.00915 (2016). 2, 3, 7, 8"},{"key":"54_CR7","unstructured":"Yu, F., Koltun, V.: Multi-scale context aggregation by dilated con-volutions. arXiv preprint arXiv:1511.07122 (2015). 2, 3, 7, 8"},{"key":"54_CR8","unstructured":"Yosinski, J., Clune, J., Bengio, Y., Lipson, H.: How transferable are features in deep neural networks? In: Advances in Neural Information Processing Systems, pp. 3320\u20133328 (2014). 1"},{"key":"54_CR9","doi-asserted-by":"crossref","unstructured":"Lin, G., Shen, C., van dan Hengel, A., Reid, I.: Efficient piecewise training of deep structured models for semantic segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016) (2016). 2, 3, 7, 8","DOI":"10.1109\/CVPR.2016.348"},{"key":"54_CR10","unstructured":"Ioffe, S., Szegedy, C.: Batch normalization: accelerating deep network training by reducing internal covariate shift. In: ICML (2015). 5"},{"key":"54_CR11","unstructured":"Shuai, B., Liu, T., Wang, G.: Improving fully convolution network for semantic segmentation. arXiv preprint arXiv:1611.08986 (2016)"},{"issue":"4","key":"54_CR12","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1109\/34.761262","volume":"21","author":"JA Shufelt","year":"1999","unstructured":"Shufelt, J.A.: Performance evaluation and analysis of monocular building extraction from aerial imagery. IEEE Trans. Pattern Anal. Mach. Intell. 21(4), 311\u2013326 (1999)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"54_CR13","doi-asserted-by":"crossref","unstructured":"Li, J., Zhang, R., Li, Y.: Multiscale convolutional neural network for the detection of built-up areas in high-resolution SAR images. In: 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE (2016)","DOI":"10.1109\/IGARSS.2016.7729230"},{"key":"54_CR14","unstructured":"Tran, P.V.: A fully convolutional neural network for cardiac segmentation in short-axis MRI. arXiv preprint arXiv:1604.00494 (2016)"},{"key":"54_CR15","unstructured":"Yu, F., Koltun, V.: Multi-scale context aggregation by dilated convolutions. arXiv preprint arXiv:1511.07122 (2015)"}],"container-title":["Lecture Notes in Computer Science","Image and Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-71598-8_54","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,29]],"date-time":"2021-12-29T01:08:52Z","timestamp":1640740132000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-71598-8_54"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319715971","9783319715988"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-71598-8_54","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"30 December 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIG","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image and Graphics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","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":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icig2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/10times.com\/icig-sa","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}