{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:24:59Z","timestamp":1750220699082,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,30]],"date-time":"2020-10-30T00:00:00Z","timestamp":1604016000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Science and Technology on Complex Electronic System Simulation Laboratory","award":["DXZF-JC-ZZ-2017-007"],"award-info":[{"award-number":["DXZF-JC-ZZ-2017-007"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,30]]},"DOI":"10.1145\/3436369.3436464","type":"proceedings-article","created":{"date-parts":[[2021,1,12]],"date-time":"2021-01-12T03:48:53Z","timestamp":1610423333000},"page":"90-95","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Asymmetric Convolution-Based Neural Network for SAR Ship Detection from Scratch"],"prefix":"10.1145","author":[{"given":"Long","family":"Han","sequence":"first","affiliation":[{"name":"Space Engineering University, Beijing China"}]},{"given":"Da","family":"Ran","sequence":"additional","affiliation":[{"name":"Space Engineering University, Beijing China"}]},{"given":"Wei","family":"Ye","sequence":"additional","affiliation":[{"name":"Space Engineering University, Beijing China"}]},{"given":"Xu","family":"Wu","sequence":"additional","affiliation":[{"name":"The Unit 32359 of PLA Xining China"}]}],"member":"320","published-online":{"date-parts":[[2021,1,11]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"e_1_3_2_1_2_1","first-page":"779","volume-title":"IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR)","author":"Redmon J.","year":"2015","unstructured":"J. Redmon , S. Divvala , R. Girshick , and A. Farhadi , \" You only look once: Unified, real-time object detection,\" in Proc . IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR) , Boston, MA, USA , Jun. 2015 , pp. 779 -- 788 . J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, \"You only look once: Unified, real-time object detection,\" in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Boston, MA, USA, Jun. 2015, pp. 779--788."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs9080860"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2923988"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs11070786"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2943241"},{"key":"e_1_3_2_1_8_1","first-page":"1911","volume-title":"IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR)","author":"Zhang X.-H.","year":"2019","unstructured":"X.-H. Zhang , Y.-C. , Guo , G.-G. Ding , J.-G. Han , \"ACNet : strengthening the kernel skeletons for powerful CNN via asymmetric convolution blocks,\" in Proc . IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR) , Long Beach, CA, USA , Jun. 2019 , pp. 1911 -- 1920 . X.-H. Zhang, Y.-C., Guo, G.-G. Ding, J.-G. Han, \"ACNet: strengthening the kernel skeletons for powerful CNN via asymmetric convolution blocks,\" in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Long Beach, CA, USA, Jun. 2019, pp. 1911--1920."},{"key":"e_1_3_2_1_9_1","first-page":"2263","volume-title":"IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR)","author":"Zhu R.","year":"2019","unstructured":"R. Zhu : Training single-shot object detectors from scratch,\" in Proc . IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR) , Jun. 2019 , pp. 2263 -- 2272 . R. Zhu et al., \"ScratchDet: Training single-shot object detectors from scratch,\" in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2019, pp. 2263--2272."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.212"},{"key":"e_1_3_2_1_11_1","volume-title":"3rd Int. Conf. Learn. Representations. (ICLR)","author":"Simonyan K.","year":"2015","unstructured":"K. Simonyan , A. Zisserman , \"Very deep convolutional networks for large-scale image recognition,\" in Proc . 3rd Int. Conf. Learn. Representations. (ICLR) , San Diego, CA, USA , May 2015 . K. Simonyan, A. Zisserman, \"Very deep convolutional networks for large-scale image recognition,\" in Proc. 3rd Int. Conf. Learn. Representations. (ICLR), San Diego, CA, USA, May 2015."},{"key":"e_1_3_2_1_12_1","first-page":"2261","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR)","author":"Huang G.","year":"2017","unstructured":"G. Huang , Z. Liu , Der Maaten L V , et al, \"Densely connected convolutional networks ,\". in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR) , Honolulu, HI, USA , Jul. 2017 , pp. 2261 -- 2269 . G. Huang, Z. Liu, Der Maaten L V, et al, \"Densely connected convolutional networks,\". in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Honolulu, HI, USA, Jul. 2017, pp. 2261--2269."},{"key":"e_1_3_2_1_13_1","first-page":"675","volume-title":"ACM Int. Conf. Multimedia","author":"Jia Y.","year":"2014","unstructured":"Y. Jia : Convolutional architecture for fast feature embedding,\" in Proc . ACM Int. Conf. Multimedia , 2014 , pp. 675 -- 678 . Y. Jia et al., \"Caffe: Convolutional architecture for fast feature embedding,\" in Proc. ACM Int. Conf. Multimedia, 2014, pp. 675--678."},{"key":"e_1_3_2_1_14_1","first-page":"1","volume-title":"Methods Appl. (BIGSARDATA)","author":"Li J.","year":"2017","unstructured":"J. Li , C. Qu , and J. Shao , \" Ship detection in SAR images based on an improved faster R-CNN,\" in Proc. SAR Big Data Era, Models , Methods Appl. (BIGSARDATA) , Nov. 2017 , pp. 1 -- 6 . J. Li, C. Qu, and J. Shao, \"Ship detection in SAR images based on an improved faster R-CNN,\" in Proc. SAR Big Data Era, Models, Methods Appl. (BIGSARDATA), Nov. 2017, pp. 1--6."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs11070765"},{"key":"e_1_3_2_1_16_1","first-page":"307","volume-title":"Proc. Informa. Commu. Tech. Conf. (ICTC)","author":"Han L.","year":"2020","unstructured":"L. Han , T-R Zheng , W. Ye , CNN Based SAR Ship Detectors\" , in Proc. Informa. Commu. Tech. Conf. (ICTC) , May 2020 , Nanjing, China , pp. 307 -- 312 . L. Han, T-R Zheng, W. Ye, et al., \"Analysis of Detection Preference to CNN Based SAR Ship Detectors\", in Proc. Informa. Commu. Tech. Conf. (ICTC), May 2020, Nanjing, China, pp. 307--312."},{"key":"e_1_3_2_1_17_1","first-page":"122","volume-title":"Proc. Eur. Conf. Comput. Vis. (ECCV)","author":"J.","year":"2018","unstructured":"Ma N, Zhang X, Zheng H, Sun J. Shufflenet v2 : Practical guidelines for efficient cnn architecture design . in Proc. Eur. Conf. Comput. Vis. (ECCV) , Munich, Germany , Sep. 2018 , pp. 122 -- 128 . Ma N, Zhang X, Zheng H, Sun J. Shufflenet v2: Practical guidelines for efficient cnn architecture design. in Proc. Eur. Conf. Comput. Vis. (ECCV), Munich, Germany, Sep. 2018, pp. 122--128."}],"event":{"name":"ICCPR 2020: 2020 9th International Conference on Computing and Pattern Recognition","sponsor":["Beijing University of Technology"],"location":"Xiamen China","acronym":"ICCPR 2020"},"container-title":["Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3436369.3436464","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3436369.3436464","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:32:51Z","timestamp":1750199571000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3436369.3436464"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,30]]},"references-count":17,"alternative-id":["10.1145\/3436369.3436464","10.1145\/3436369"],"URL":"https:\/\/doi.org\/10.1145\/3436369.3436464","relation":{},"subject":[],"published":{"date-parts":[[2020,10,30]]},"assertion":[{"value":"2021-01-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}