{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T04:46:26Z","timestamp":1745901986771,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031113482"},{"type":"electronic","value":"9783031113499"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-11349-9_26","type":"book-chapter","created":{"date-parts":[[2022,7,23]],"date-time":"2022-07-23T17:06:46Z","timestamp":1658596006000},"page":"299-307","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Towards Semi-supervised Tree Canopy Detection and Extraction from UAV Images"],"prefix":"10.1007","author":[{"given":"Uttam","family":"Kumar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anindita","family":"Dasgupta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingamallu S. N.","family":"Venkata Vamsi Krishna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pranav Kumar","family":"Chintakunta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,24]]},"reference":[{"key":"26_CR1","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: Unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"26_CR2","unstructured":"Redmon, J., Farhadi, A.: Yolov3: An incremental improvement. arXiv preprint arXiv:1804.02767 (2018)"},{"key":"26_CR3","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"26_CR4","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: Towards real-time object detection with region proposal networks. In: Proceedings of the 28th International Conference on Neural Information Processing Systems \u2013 NIPS\u201915, vol. 1, pp. 91\u201399. Cambridge, MA, USA, MIT Press (2015)"},{"key":"26_CR5","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., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science, vol. 9351. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"26_CR6","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask r-cnn. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"issue":"16","key":"26_CR7","doi-asserted-by":"publisher","first-page":"3595","DOI":"10.3390\/s19163595","volume":"19","author":"AAD Santos","year":"2019","unstructured":"Santos, A.A.D., et al.: Assessment of cnn-based methods for individual tree detection on images captured by rgb cameras attached to UAVs. Sensors 19(16), 3595 (2019)","journal-title":"Sensors"},{"issue":"11","key":"26_CR8","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.3390\/rs11111309","volume":"11","author":"BG Weinstein","year":"2019","unstructured":"Weinstein, B.G., Marconi, S., Bohlman, S., Zare, A., White, E.: Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks. Remote Sensing 11(11), 1309 (2019)","journal-title":"Remote Sensing"},{"issue":"5","key":"26_CR9","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1080\/07038992.2016.1196582","volume":"42","author":"CA Silva","year":"2016","unstructured":"Silva, C.A., et al.: Imputation of individual longleaf pine (Pinus palustris mill.) tree attributes from field and lidar data. Can. J. Remote Sens. 42(5), 554\u2013573 (2016)","journal-title":"Can. J. Remote Sens."},{"key":"26_CR10","volume":"56","author":"BG Weinstein","year":"2020","unstructured":"Weinstein, B.G., Marconi, S., Bohlman, S.A., Zare, A., White, E.P.: Cross-site learning in deep learning RGB tree crown detection. EcologicalInformatics 56, 101061 (2020)","journal-title":"EcologicalInformatics"},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Roslan, Z., Long, Z.A., Ismail, R.: Individual tree crown detectionusing GAN and RetinaNet on tropical forest. In: 2021 15th International Conference on Ubiquitous Information Management and Communication (IMCOM), pp. 1\u20137. IEEE (2021)","DOI":"10.1109\/IMCOM51814.2021.9377360"},{"issue":"3","key":"26_CR12","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1007\/s12524-020-01240-2","volume":"49","author":"A Adhikari","year":"2021","unstructured":"Adhikari, A., Kumar, M., Agrawal, S., Raghavendra, S.: An integrated object and machine learning approach for tree canopy extraction from UAV datasets. J. Indian Soc. Remote Sens. 49(3), 471\u2013478 (2021)","journal-title":"J. Indian Soc. Remote Sens."},{"issue":"9","key":"26_CR13","doi-asserted-by":"publisher","first-page":"1795","DOI":"10.3390\/rs13091795","volume":"13","author":"Y Guo","year":"2021","unstructured":"Guo, Y., et al.: Integrating spectral and textural information for monitoring the growth of pear trees using optical images from the UAV platform. Remote Sens. 13(9), 1795 (2021)","journal-title":"Remote Sens."},{"issue":"3","key":"26_CR14","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1007\/s12524-020-01227-z","volume":"49","author":"A Agarwal","year":"2021","unstructured":"Agarwal, A., Kumar, S., Singh, D.: An adaptive techniqueto detect and remove shadow from drone data. J. Indian Soc. Remote Sens. 49(3), 491\u2013498 (2021)","journal-title":"J. Indian Soc. Remote Sens."},{"issue":"1","key":"26_CR15","doi-asserted-by":"publisher","first-page":"259","DOI":"10.13031\/2013.27838","volume":"38","author":"DM Woebbecke","year":"1995","unstructured":"Woebbecke, D.M., Meyer, G.E., Von Bargen, K., Mortensen, D.A.: Color indices for weed identification under various soil, residue, and lighting conditions. Trans. ASAE 38(1), 259\u2013269 (1995)","journal-title":"Trans. ASAE"},{"issue":"2","key":"26_CR16","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.compag.2008.03.009","volume":"63","author":"GE Meyer","year":"2008","unstructured":"Meyer, G.E., Neto, J.C.: Verification of color vegetation indices for automated crop imaging applications. Comput. Electron. Agric. 63(2), 282\u2013293 (2008)","journal-title":"Comput. Electron. Agric."},{"key":"26_CR17","unstructured":"Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., & S\u00fcsstrunk, S.: SLIC superpixels. Tech. Rep. 149300, EcolePolytechnique F\u00e9d\u00e9ral de Lausssanne (EPFL) (2010)"},{"key":"26_CR18","doi-asserted-by":"crossref","unstructured":"Kanezaki, A.: Unsupervised image segmentation by backpropagation. In: 2018 IEEE international conference on acoustics, speech and signal processing (ICASSP), pp. 1543\u20131547. IEEE (2018)","DOI":"10.1109\/ICASSP.2018.8462533"},{"key":"26_CR19","unstructured":"Tzutalin. Labelimg. https:\/\/github.com\/tzutalin\/labelImg (2015)"},{"key":"26_CR20","doi-asserted-by":"crossref","unstructured":"Dutta, A., Zisserman, A.: The via annotation software for images, audio and video. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 2276\u20132279 (2019)","DOI":"10.1145\/3343031.3350535"},{"issue":"3","key":"26_CR21","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1007\/s12524-020-01229-x","volume":"49","author":"AA Micheal","year":"2020","unstructured":"Micheal, A.A., Vani, K., Sanjeevi, S., Lin, C.-H.: Object detection and tracking with UAV data using deep learning. J. Indian Soc. Remote Sens. 49(3), 463\u2013469 (2020)","journal-title":"J. Indian Soc. Remote Sens."}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-11349-9_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,23]],"date-time":"2022-07-23T17:10:17Z","timestamp":1658596217000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-11349-9_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031113482","9783031113499"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-11349-9_26","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"24 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rupnagar","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":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iitrpr.cvip2021.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"260","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"77","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}