{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T05:18:32Z","timestamp":1767849512844,"version":"3.49.0"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61673396"],"award-info":[{"award-number":["61673396"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61976245"],"award-info":[{"award-number":["61976245"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1007\/s13042-022-01514-w","type":"journal-article","created":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T10:02:56Z","timestamp":1646128976000},"page":"2189-2197","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Global contextual attention for pure regression object detection"],"prefix":"10.1007","volume":"13","author":[{"given":"Bingbing","family":"Fan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7323-5896","authenticated-orcid":false,"given":"Mingwen","family":"Shao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunhao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cunhe","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,1]]},"reference":[{"key":"1514_CR1","doi-asserted-by":"crossref","unstructured":"Cai ZW, Vasconcelos N (2018) Cascade R-CNN: delving into high quality object detection In: IEEE conference on computer vision and pattern recognition (CVPR), pp 6154\u20136162","DOI":"10.1109\/CVPR.2018.00644"},{"key":"1514_CR2","doi-asserted-by":"crossref","unstructured":"Cao Y, Xu JR, Lin S, Wei FY, Hu H (2019) Gcnet: Non-local networks meet squeeze-excitation networks and beyond. In: IEEE international conference on computer vision (ICCV), pp 1971\u20131980","DOI":"10.1109\/ICCVW.2019.00246"},{"key":"1514_CR3","unstructured":"Chen K, Wang JQ, Pang JM, Cao YH, Xiong Y, Li XX (2019) Mmdetection: Open mmlab detection toolbox and benchmark. arXiv preprint arXiv:1906.07155"},{"key":"1514_CR4","doi-asserted-by":"crossref","unstructured":"Cho K, Merrienboer BV, Bahdanau D (2014) Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Empirical methods in natural language processing (EMNLP), pp 1724\u20131734","DOI":"10.3115\/v1\/D14-1179"},{"key":"1514_CR5","unstructured":"Dai JF, Li Y, He KM, Sun J (2016) R-FCN: object detection via region-based fully convolutional networks. In: Neural information processing systems (NIPS), pp 379\u2013387"},{"key":"1514_CR6","doi-asserted-by":"crossref","unstructured":"Dai JF, Qi HZ, Xiong YW, Li Y, Zhang GD, Hu H, Wei YC (2017) Deformable convolutional networks. In: IEEE international conference on computer vision (ICCV), pp 764\u2013773","DOI":"10.1109\/ICCV.2017.89"},{"key":"1514_CR7","doi-asserted-by":"crossref","unstructured":"Gehring J, Auli M, Grangier D, and Dauphin YN (2017) A convolutional encoder model for neural machine translation. In: Association for Computational Linguistics (ACL), pp 123\u2013135","DOI":"10.18653\/v1\/P17-1012"},{"key":"1514_CR8","doi-asserted-by":"crossref","unstructured":"Girshick RB (2015) Fast R-CNN. In: IEEE international conference on computer vision (ICCV), pp 1440\u20131448","DOI":"10.1109\/ICCV.2015.169"},{"key":"1514_CR9","doi-asserted-by":"crossref","unstructured":"He KM, Gkioxari G, Girshick R (2017) Mask R-CNN. In: IEEE international conference on computer vision (ICCV), pp 2980\u20132988","DOI":"10.1109\/ICCV.2017.322"},{"issue":"9","key":"1514_CR10","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"KM He","year":"2015","unstructured":"He KM, Zhang XY, Ren SQ, Sun J (2015) Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans Pattern Anal Mach Intell 37(9):1904\u20131916","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1514_CR11","doi-asserted-by":"crossref","unstructured":"Hu H, Gu JY, Zhang Z, Dai JF, Wei YC (2017) Relation networks for object detection. arXiv preprint arXiv:1711.11575","DOI":"10.1109\/CVPR.2018.00378"},{"key":"1514_CR12","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"1514_CR13","doi-asserted-by":"crossref","unstructured":"Huang ZL, Wang XG, Huang LC, Huang C, Wei YC, Liu WY (2019) Ccnet: Criss-cross attention for semantic segmentation. In: IEEE international conference on computer vision (ICCV), pp 603\u2013612","DOI":"10.1109\/ICCV.2019.00069"},{"key":"1514_CR14","doi-asserted-by":"crossref","unstructured":"Kong T, Sun FC, Liu HP, Jiang YN, Shi JB (2019) Foveabox: Beyond anchor-based object detector. arXiv preprint arXiv:1904.03797","DOI":"10.1109\/TIP.2020.3002345"},{"key":"1514_CR15","doi-asserted-by":"crossref","unstructured":"Law H, Deng J (2018) Cornernet: Detecting objects as paired keypoints. In: European conference on computer vision (ECCV), pp 765\u2013781","DOI":"10.1007\/978-3-030-01264-9_45"},{"issue":"5","key":"1514_CR16","doi-asserted-by":"publisher","first-page":"944","DOI":"10.1109\/TMM.2016.2642789","volume":"19","author":"JN Li","year":"2017","unstructured":"Li JN, Wei YC, Liang XD, Dong J, Xu TF (2017) Attentive contexts for object detection. IEEE Trans Multimedia 19(5):944\u2013954","journal-title":"IEEE Trans Multimedia"},{"key":"1514_CR17","doi-asserted-by":"crossref","unstructured":"Lin TY, Doll\u00e1r P, Girshick R, He KM (2017) Feature pyramid networks for object detection. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 936\u2013944","DOI":"10.1109\/CVPR.2017.106"},{"issue":"2","key":"1514_CR18","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","volume":"42","author":"TY Lin","year":"2020","unstructured":"Lin TY, Goyal P, Girshick R, He KM (2020) Focal loss for dense object detection. IEEE Trans Pattern Anal Mach Intell 42(2):318\u2013327","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1514_CR19","doi-asserted-by":"crossref","unstructured":"Lin TY, Maire M, Belongie S, Hays J (2014) Microsoft COCO: common objects in context. In: European conference on computer vision (ECCV), pp 740\u2013755","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"1514_CR20","doi-asserted-by":"crossref","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S (2016) SSD: single shot multibox detector. In: European conference on computer vision (ECCV), pp 21\u201337","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"1514_CR21","doi-asserted-by":"crossref","unstructured":"Pato L, Negrinho RM, Aguiar PM (2020) Seeing without looking: Contextual rescoring of object detections for AP maximization. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 14598\u201314606","DOI":"10.1109\/CVPR42600.2020.01462"},{"key":"1514_CR22","unstructured":"Pinheiro PH, Collobert R, Doll\u00e1r P (2015) Learning to segment object candidates. In: Neural information processing systems (NIPS), pp 1990\u20131998"},{"key":"1514_CR23","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala SK, Girshick R, Farhadi A (2016) You only look once: Unified, real-time object detection. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 779\u2013788","DOI":"10.1109\/CVPR.2016.91"},{"key":"1514_CR24","unstructured":"Redmon J, Farhadi A (2018) Yolov3: An incremental improvement. arXiv preprint arXiv:1804.02767"},{"key":"1514_CR25","unstructured":"Ren SQ, He KM, Girshick R, Sun J (2015) Faster R-CNN: towards real-time object detection with region proposal networks. In: Neural information processing systems (NIPS), pp 91\u201399"},{"key":"1514_CR26","doi-asserted-by":"crossref","unstructured":"Stewart R, Andriluka M (2016) End-to-end people detection in crowded scenes. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 2325\u20132333","DOI":"10.1109\/CVPR.2016.255"},{"key":"1514_CR27","doi-asserted-by":"crossref","unstructured":"Tian Z, Shen CH, Chen H, He T (2019) FCOS: fully convolutional one-stage object detection. In: IEEE international conference on computer vision (ICCV), pp 9626\u20139635","DOI":"10.1109\/ICCV.2019.00972"},{"key":"1514_CR28","doi-asserted-by":"crossref","unstructured":"Toshev A, Szegedy C (2014) Deeppose: Human pose estimation via deep neural networks. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 1653\u20131660","DOI":"10.1109\/CVPR.2014.214"},{"key":"1514_CR29","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J (2017) Attention is all you need. In: Neural information processing systems (NIPS), pp 5998\u20136008"},{"key":"1514_CR30","doi-asserted-by":"crossref","unstructured":"Wang XL, Girshick R, Gupta A, He KM (2018) Non-local neural networks. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 7794\u20137803","DOI":"10.1109\/CVPR.2018.00813"},{"key":"1514_CR31","doi-asserted-by":"crossref","unstructured":"Xu H, Jiang CH, Liang XD, Lin L, Li ZG (2019) Reasoning-RCNN: Unifying adaptive global reasoning into large-scale object detection. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 6419\u20136428","DOI":"10.1109\/CVPR.2019.00658"},{"key":"1514_CR32","doi-asserted-by":"crossref","unstructured":"Yang Z, Liu SH, Hu H, Wang LW, Lin S (2019) Reppoints: Point set representation for object detection. In: IEEE international conference on computer vision (ICCV), pp 9656\u20139665","DOI":"10.1109\/ICCV.2019.00975"},{"key":"1514_CR33","unstructured":"Zhou XY, Wang DQ, Kr\u00e4henb\u00fchl P (2019) Objects as points. arXiv preprint arXiv:1904.07850"},{"key":"1514_CR34","doi-asserted-by":"crossref","unstructured":"Zhou XY, Zhuo JC, Kr\u00e4henb\u00fchl P (2019) Bottom-up object detection by grouping extreme and center points. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 850\u2013859","DOI":"10.1109\/CVPR.2019.00094"},{"key":"1514_CR35","doi-asserted-by":"crossref","unstructured":"Zhu CC, He YH, Savvides M (2019) Feature selective anchor-free module for single-shot object detection. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 840\u2013849","DOI":"10.1109\/CVPR.2019.00093"},{"key":"1514_CR36","doi-asserted-by":"crossref","unstructured":"Ke W, Zhang TL, Huang ZY, Ye QX, Liu ZJ, Huang D (2020) Multiple anchor learning for visual object detection In: IEEE conference on computer vision and pattern recognition (CVPR), pp 10203\u201310212","DOI":"10.1109\/CVPR42600.2020.01022"},{"key":"1514_CR37","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.ins.2020.12.013","volume":"554","author":"MW Shao","year":"2021","unstructured":"Shao MW, Zhang GZ, Zuo WM, Meng DY (2021) Target attack on biomedical image segmentation model based on multi-scale gradients. Inf Sci 554:33\u201346","journal-title":"Inf Sci"},{"key":"1514_CR38","doi-asserted-by":"crossref","unstructured":"Li YH, Shao MW, Fan BB, Zhang W (2021) Multi-scale global context feature pyramid network for object detector. Signal Image Video Pro 1-9","DOI":"10.1007\/s11760-021-02010-4"},{"issue":"12","key":"1514_CR39","doi-asserted-by":"publisher","first-page":"1551","DOI":"10.1631\/FITEE.2100463","volume":"22","author":"Y Yang","year":"2021","unstructured":"Yang Y, Zhuang YT, Pan YH (2021) Multiple knowledge representation for big data artificial intelligence: framework, applications, and case studies. Front Inf Technol Electr Eng 22(12):1551\u20131684","journal-title":"Front Inf Technol Electr Eng"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01514-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-022-01514-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01514-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,29]],"date-time":"2022-06-29T08:27:03Z","timestamp":1656491223000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-022-01514-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,1]]},"references-count":39,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["1514"],"URL":"https:\/\/doi.org\/10.1007\/s13042-022-01514-w","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,1]]},"assertion":[{"value":"17 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 January 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 March 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}