{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:12:16Z","timestamp":1750219936627,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,19]],"date-time":"2022-08-19T00:00:00Z","timestamp":1660867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,19]]},"DOI":"10.1145\/3563737.3563740","type":"proceedings-article","created":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T14:04:27Z","timestamp":1669039467000},"page":"12-18","source":"Crossref","is-referenced-by-count":0,"title":["Semi-supervised learning with double head approach for carotid artery detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2439-5217","authenticated-orcid":false,"given":"Zhiwei","family":"Li","sequence":"first","affiliation":[{"name":"School of Data Science and Engineering, East China Normal University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Peng","sequence":"additional","affiliation":[{"name":"Information Technology Services, East China Normal University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changquan","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Data Science and Engineering, East China Normal University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,11,21]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"587","volume-title":"IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press","author":"Girshick R.","year":"2014","unstructured":"R. Girshick , J. Donahue , T. Darrell and J. Malik , Rich feature hierarchies for accurate object detection and semantic segmentation , IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press , 2014 ), pp. 580\u2013 587 . R. Girshick, J. Donahue, T. Darrell and J. Malik, Rich feature hierarchies for accurate object detection and semantic segmentation, IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press, 2014), pp. 580\u2013587."},{"key":"e_1_3_2_1_2_1","first-page":"1448","volume-title":"IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press","author":"Girshick R.","year":"2015","unstructured":"R. Girshick , Fast r-cnn , IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press , 2015 ), pp. 1440\u2013 1448 . R. Girshick, Fast r-cnn, IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press, 2015), pp. 1440\u20131448."},{"key":"e_1_3_2_1_3_1","first-page":"99","volume-title":"Advances in Neural","author":"Ren S.","year":"2015","unstructured":"S. Ren , K. He , R. Girshick and J. Sun , Faster r-cnn: Towards real-time object detection with region proposal networks , Advances in Neural Information Processing Systems (NeurIPS) (MIT Press , 2015 ), pp. 91\u2013 99 . S. Ren, K. He, R. Girshick and J. Sun, Faster r-cnn: Towards real-time object detection with region proposal networks, Advances in Neural Information Processing Systems (NeurIPS) (MIT Press, 2015), pp. 91\u201399."},{"key":"e_1_3_2_1_4_1","first-page":"8","author":"Li Hailiang","year":"2018","unstructured":"Hailiang Li , Jian Weng , Yujian Shi , Wanrong Gu , Yijun Mao , Yonghua Wang , Weiwei Liu , Jiajie Zhang , An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images , Sci. Rep. 8 ( 2018 ). Hailiang Li, Jian Weng, Yujian Shi, Wanrong Gu, Yijun Mao, Yonghua Wang, Weiwei Liu, Jiajie Zhang, An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images, Sci. Rep. 8 (2018).","journal-title":"Sci. Rep."},{"key":"e_1_3_2_1_5_1","volume-title":"Workshop of ICML","author":"Lee Dong-Hyun","year":"2013","unstructured":"Dong-Hyun Lee Pseudo-label : The simple and efficient semi-supervised learning method for deep neural networks . In Workshop of ICML , 2013 . Dong-Hyun Lee Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks. In Workshop of ICML, 2013."},{"key":"e_1_3_2_1_6_1","first-page":"2125","volume-title":"IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press","author":"Lin T. Y.","year":"2017","unstructured":"T. Y. Lin , P. Dollar , R. Girshick , K. He , B. Hariharan and S. Belongie , Feature pyramid networks for object detection , IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press , 2017 ), pp. 2117\u2013 2125 . T. Y. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan and S. Belongie, Feature pyramid networks for object detection, IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press, 2017), pp. 2117\u20132125."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"issue":"3","key":"e_1_3_2_1_8_1","first-page":"559","volume":"67","author":"Welker M.J.","year":"2003","unstructured":"M.J. Welker , D. Orlov , Thyroid nodules , Am. Fam. Physician 67 ( 3 ) ( 2003 ) 559 \u2013 566 . M.J. Welker, D. Orlov, Thyroid nodules, Am. Fam. Physician 67 (3) (2003) 559\u2013566.","journal-title":"Am. Fam. Physician"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Yue Wu \u00a0Yinpeng Chen \u00a0Lu Yuan \u00a0Zicheng Liu \u00a0Lijuan Wang \u00a0Hongzhi Li \u00a0Yun Fu. Rethinking Classification and Localization for Object Detection.\u00a0CVPR\u00a02020:\u00a010183-10192  Yue Wu \u00a0Yinpeng Chen \u00a0Lu Yuan \u00a0Zicheng Liu \u00a0Lijuan Wang \u00a0Hongzhi Li \u00a0Yun Fu. Rethinking Classification and Localization for Object Detection.\u00a0CVPR\u00a02020:\u00a010183-10192","DOI":"10.1109\/CVPR42600.2020.01020"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Shu Liu \u00a0Lu Qi \u00a0Haifang Qin \u00a0Jianping Shi \u00a0Jiaya Jia. Path\u00a0Aggregation\u00a0Network\u00a0for\u00a0Instance\u00a0Segmentation.\u00a0CVPR\u00a02018:\u00a08759-8768  Shu Liu \u00a0Lu Qi \u00a0Haifang Qin \u00a0Jianping Shi \u00a0Jiaya Jia. Path\u00a0Aggregation\u00a0Network\u00a0for\u00a0Instance\u00a0Segmentation.\u00a0CVPR\u00a02018:\u00a08759-8768","DOI":"10.1109\/CVPR.2018.00913"},{"key":"e_1_3_2_1_11_1","unstructured":"Kai Chen \u00a0Jiaqi Wang \u00a0Jiangmiao Pang \u00a0Yuhang Cao \u00a0Yu Xiong \u00a0Xiaoxiao Li \u00a0Shuyang Sun \u00a0Wansen Feng \u00a0Ziwei Liu \u00a0Jiarui Xu \u00a0Zheng Zhang \u00a0Dazhi Cheng \u00a0Chenchen Zhu \u00a0Tianheng Cheng \u00a0Qijie Zhao \u00a0Buyu Li \u00a0Xin Lu \u00a0Rui Zhu \u00a0Yue Wu \u00a0Jifeng Dai \u00a0Jingdong Wang \u00a0Jianping Shi \u00a0Wanli Ouyang \u00a0Chen Change Loy \u00a0Dahua Lin: MMDetection: Open MMLab Detection Toolbox and Benchmark.\u00a0CoRR\u00a0abs\/1906.07155\u00a0(2019)  Kai Chen \u00a0Jiaqi Wang \u00a0Jiangmiao Pang \u00a0Yuhang Cao \u00a0Yu Xiong \u00a0Xiaoxiao Li \u00a0Shuyang Sun \u00a0Wansen Feng \u00a0Ziwei Liu \u00a0Jiarui Xu \u00a0Zheng Zhang \u00a0Dazhi Cheng \u00a0Chenchen Zhu \u00a0Tianheng Cheng \u00a0Qijie Zhao \u00a0Buyu Li \u00a0Xin Lu \u00a0Rui Zhu \u00a0Yue Wu \u00a0Jifeng Dai \u00a0Jingdong Wang \u00a0Jianping Shi \u00a0Wanli Ouyang \u00a0Chen Change Loy \u00a0Dahua Lin: MMDetection: Open MMLab Detection Toolbox and Benchmark.\u00a0CoRR\u00a0abs\/1906.07155\u00a0(2019)"},{"key":"e_1_3_2_1_12_1","unstructured":"Alex Krizhevsky \u00a0Ilya Sutskever \u00a0Geoffrey E. Hinton: ImageNet\u00a0Classification\u00a0with\u00a0Deep\u00a0Convolutional Neural Networks.\u00a0NIPS\u00a02012:\u00a01106-1114  Alex Krizhevsky \u00a0Ilya Sutskever \u00a0Geoffrey E. Hinton: ImageNet\u00a0Classification\u00a0with\u00a0Deep\u00a0Convolutional Neural Networks.\u00a0NIPS\u00a02012:\u00a01106-1114"},{"volume-title":"The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","year":"2018","key":"e_1_3_2_1_13_1","unstructured":"ZhaoweiCaiandNunoVasconcelos.Cascader-cnn:Delving into high quality object detection . In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018 . ZhaoweiCaiandNunoVasconcelos.Cascader-cnn:Delving into high quality object detection. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2018."},{"key":"e_1_3_2_1_14_1","first-page":"2988","volume-title":"Computer Vision (ICCV), 2017 IEEE International Conference on","author":"He Kaiming","unstructured":"Kaiming He , Georgia Gkioxari , Piotr Dolla \u0301r , and Ross Gir- shick. Mask r-cnn . In Computer Vision (ICCV), 2017 IEEE International Conference on , pages 2980\u2013 2988 . IEEE, 2017. Kaiming He, Georgia Gkioxari, Piotr Dolla \u0301r, and Ross Gir- shick. Mask r-cnn. In Computer Vision (ICCV), 2017 IEEE International Conference on, pages 2980\u20132988. IEEE, 2017."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Zhaojin Huang \u00a0Lichao Huang \u00a0Yongchao Gong \u00a0Chang Huang \u00a0Xinggang Wang: Mask\u00a0Scoring\u00a0R-CNN.\u00a0CVPR\u00a02019:\u00a06409-6418  Zhaojin Huang \u00a0Lichao Huang \u00a0Yongchao Gong \u00a0Chang Huang \u00a0Xinggang Wang: Mask\u00a0Scoring\u00a0R-CNN.\u00a0CVPR\u00a02019:\u00a06409-6418","DOI":"10.1109\/CVPR.2019.00657"},{"key":"e_1_3_2_1_16_1","volume-title":"The IEEE International Conference on Computer Vision (ICCV)","author":"Zhang Haichao","year":"2019","unstructured":"Haichao Zhang and Jianyu Wang . Towards adversarially ro- bust object detection . In The IEEE International Conference on Computer Vision (ICCV) , October 2019 . Haichao Zhang and Jianyu Wang. Towards adversarially ro- bust object detection. In The IEEE International Conference on Computer Vision (ICCV), October 2019."},{"key":"e_1_3_2_1_17_1","volume-title":"The IEEE International Conference on Computer Vision (ICCV)","author":"Li Yanghao","year":"2019","unstructured":"Yanghao Li , Yuntao Chen , Naiyan Wang , and Zhaoxiang Zhang . Scale-aware trident networks for object detection . In The IEEE International Conference on Computer Vision (ICCV) , October 2019 . Yanghao Li, Yuntao Chen, Naiyan Wang, and Zhaoxiang Zhang. Scale-aware trident networks for object detection. In The IEEE International Conference on Computer Vision (ICCV), October 2019."},{"key":"e_1_3_2_1_18_1","volume-title":"International Conference on Learning Representations","author":"Simonyan K.","year":"2015","unstructured":"K. Simonyan and A. Zisserman . Very deep convolutional networks for large-scale image recognition . In International Conference on Learning Representations , 2015 . K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. In International Conference on Learning Representations, 2015."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"e_1_3_2_1_21_1","first-page":"893","volume-title":"IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press","author":"Dalal","year":"2005","unstructured":"N, Dalal and B, Triggs , Histograms of oriented gradients for human detection , IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press , 2005 ), pp. 886\u2013 893 . N, Dalal and B, Triggs, Histograms of oriented gradients for human detection, IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (IEEE Press, 2005), pp. 886\u2013893."}],"event":{"name":"ICBIP 2022: 2022 7th International Conference on Biomedical Signal and Image Processing","acronym":"ICBIP 2022","location":"Suzhou China"},"container-title":["2022 7th International Conference on Biomedical Signal and Image Processing (ICBIP)"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3563737.3563740","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3563737.3563740","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:48:50Z","timestamp":1750182530000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3563737.3563740"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,19]]},"references-count":21,"alternative-id":["10.1145\/3563737.3563740","10.1145\/3563737"],"URL":"https:\/\/doi.org\/10.1145\/3563737.3563740","relation":{},"subject":[],"published":{"date-parts":[[2022,8,19]]}}}