{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:31:20Z","timestamp":1743103880527,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030882068"},{"type":"electronic","value":"9783030882075"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-88207-5_15","type":"book-chapter","created":{"date-parts":[[2021,9,30]],"date-time":"2021-09-30T12:20:08Z","timestamp":1633004408000},"page":"150-159","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Graph Attention Network Based Object Detection and Classification in Crowded Scenario"],"prefix":"10.1007","author":[{"given":"Guangyuan","family":"Xu","sequence":"first","affiliation":[]},{"given":"Shaungxi","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,1]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Bodla, N., Singh, B., Chellappa, R., Davis, L.S.: Soft-NMS: improving object detection with one line of code. In: ICCV 2017 (2017)","DOI":"10.1109\/ICCV.2017.593"},{"key":"15_CR2","doi-asserted-by":"publisher","unstructured":"Jiang, B., Luo, R., Mao, J.: Acquisition of localization confidence for accurate object detection. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11218, pp. 816\u2012832 (2018). https:\/\/doi.org\/10.1007\/978-3-030-01264-9_48","DOI":"10.1007\/978-3-030-01264-9_48"},{"key":"15_CR3","doi-asserted-by":"crossref","unstructured":"He, Y., Zhu, C., Wang, J.: Softer-NMS: rethinking bounding box regression for accurate object detection. In: CVPR 2019 (2019)","DOI":"10.1109\/CVPR.2019.00300"},{"key":"15_CR4","doi-asserted-by":"publisher","unstructured":"Hosang, J., Benenson, R., Schiele, B.: A convnet for non-maximum suppression. In: GCPR 2016. LNCS, vol. 9796, pp. 192\u2012204. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-45886-1_16","DOI":"10.1007\/978-3-319-45886-1_16"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Hosang, J.H., Benenson, R., Schiele, B.: Learning non-maximum suppression. In: CVPR 2017 (2017)","DOI":"10.1109\/CVPR.2017.685"},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Liu,S., Huang, D., Wang, Y.: Adaptive NMS: refining pedestrian detection in a crowd. In: CVPR 2019 (2019)","DOI":"10.1109\/CVPR.2019.00662"},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Neubeck, A., Van Gool, L.J.: Efficient non-maximum suppression (2006)","DOI":"10.1109\/ICPR.2006.479"},{"key":"15_CR8","unstructured":"Zhou, J., et al.: Graph neural networks: a review of methods and applications (2018)"},{"key":"15_CR9","unstructured":"Wu, Z., et al.: A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst. 99, 1\u201321"},{"key":"15_CR10","unstructured":"Bruna, J., Zaremba, W., Szlam, A., LeCun, Y.: Spectral networks and locally connected networks on graphs. In: Proceedings of ICLR (2014)"},{"key":"15_CR11","unstructured":"Henaff, M., Bruna, J., LeCun, Y.: Deep convolutional networks on graph-structured data. arXiv preprint arXiv:1506.05163 (2015)"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: CVPR 2014 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Cai, Z., Vasconcelos, N.: Cascade R-CNN: Delving into High Quality Object Detection (2017)","DOI":"10.1109\/CVPR.2018.00644"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Ren, S., He, K., Girshick, R.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"15_CR15","doi-asserted-by":"crossref","unstructured":"Redmon, J., et al.: You only look once: unified, real-time object detection. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE 2016 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"15_CR16","doi-asserted-by":"publisher","unstructured":"Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21\u201237. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"15_CR17","doi-asserted-by":"crossref","unstructured":"Redmon, J., Farhadi, A.: YOLO9000: better, faster, stronger. In: CVPR 2017 (2017)","DOI":"10.1109\/CVPR.2017.690"},{"key":"15_CR18","unstructured":"Redmon, J., Farhadi, A.: YOLOv3: an incremental improvement (2018)"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast R-CNN. In: 2015 IEEE International Conference on Computer Vision (ICCV). IEEE 2016 (2016)","DOI":"10.1109\/ICCV.2015.169"},{"key":"15_CR20","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., et al.: Feature Pyramid Networks for Object Detection (2016)","DOI":"10.1109\/CVPR.2017.106"},{"key":"15_CR21","doi-asserted-by":"crossref","unstructured":"Liu, S., et al.: Path Aggregation Network for Instance Segmentation (2018)","DOI":"10.1109\/CVPR.2018.00913"}],"container-title":["Lecture Notes in Computer Science","Cooperative Design, Visualization, and Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-88207-5_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,7]],"date-time":"2022-02-07T15:03:27Z","timestamp":1644246207000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-88207-5_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030882068","9783030882075"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-88207-5_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"1 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CDVE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Cooperative Design, Visualization and Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cdve2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.cdve.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"69","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":"25","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":"9","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":"36% - 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":"2.5","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)"}}]}}