{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:27:34Z","timestamp":1750220854503,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T00:00:00Z","timestamp":1567987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2016YFB0502600"],"award-info":[{"award-number":["2016YFB0502600"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,9,9]]},"DOI":"10.1145\/3349801.3349819","type":"proceedings-article","created":{"date-parts":[[2019,9,25]],"date-time":"2019-09-25T12:58:02Z","timestamp":1569416282000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["PLFCN"],"prefix":"10.1145","author":[{"given":"Shuo","family":"Liu","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, Beihang University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenrui","family":"Ding","sequence":"additional","affiliation":[{"name":"Unmanned System Research Institute, Beihang University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongguang","family":"Li","sequence":"additional","affiliation":[{"name":"Unmanned System Research Institute, Beihang University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunlei","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Beihang University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,9,9]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"[n.d.]. ISPRS 2D semantic labeling contest. http:\/\/www2.isprs.org\/commissions\/comm3\/wg4\/2d-sem-label-vaihingen.html.  [n.d.]. ISPRS 2D semantic labeling contest. http:\/\/www2.isprs.org\/commissions\/comm3\/wg4\/2d-sem-label-vaihingen.html."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Vijay Badrinarayanan Alex Kendall and Roberto Cipolla. 2017. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Scene Segmentation.  Vijay Badrinarayanan Alex Kendall and Roberto Cipolla. 2017. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Scene Segmentation.","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"e_1_3_2_1_3_1","unstructured":"Liangchieh Chen George Papandreou Iasonas Kokkinos Kevin P Murphy and Alan L Yuille. 2015. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs.  Liangchieh Chen George Papandreou Iasonas Kokkinos Kevin P Murphy and Alan L Yuille. 2015. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Liangchieh Chen George Papandreou Iasonas Kokkinos Kevin P Murphy and Alan L Yuille. 2018. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets Atrous Convolution and Fully Connected CRFs.  Liangchieh Chen George Papandreou Iasonas Kokkinos Kevin P Murphy and Alan L Yuille. 2018. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets Atrous Convolution and Fully Connected CRFs.","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Dongcai Cheng Gaofeng Meng Shiming Xiang and Chunhong Pan. 2017. FusionNet: Edge Aware Deep Convolutional Networks for Semantic Segmentation of Remote Sensing Harbor Images.  Dongcai Cheng Gaofeng Meng Shiming Xiang and Chunhong Pan. 2017. FusionNet: Edge Aware Deep Convolutional Networks for Semantic Segmentation of Remote Sensing Harbor Images.","DOI":"10.1109\/JSTARS.2017.2747599"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"David Eigen and Rob Fergus. 2016. Predicting Depth Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture.  David Eigen and Rob Fergus. 2016. Predicting Depth Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture.","DOI":"10.1109\/ICCV.2015.304"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Alberto Garciagarcia Sergio Ortsescolano Sergiu Oprea Victor Villenamartinez and Jose Garcia Rodriguez. 2017. A Review on Deep Learning Techniques Applied to Semantic Segmentation.  Alberto Garciagarcia Sergio Ortsescolano Sergiu Oprea Victor Villenamartinez and Jose Garcia Rodriguez. 2017. A Review on Deep Learning Techniques Applied to Semantic Segmentation.","DOI":"10.1016\/j.asoc.2018.05.018"},{"key":"e_1_3_2_1_8_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification.  Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Qibin Hou Mingming Cheng Xiaowei Hu Ali Borji Zhuowen Tu and Philip H S Torr. 2017. Deeply Supervised Salient Object Detection with Short Connections.  Qibin Hou Mingming Cheng Xiaowei Hu Ali Borji Zhuowen Tu and Philip H S Torr. 2017. Deeply Supervised Salient Object Detection with Short Connections.","DOI":"10.1109\/CVPR.2017.563"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"e_1_3_2_1_11_1","volume-title":"Arnt B\u00c3\u00ffrre Salberg, and Robert Jenssen","author":"Kampffmeyer Michael","year":"2016","unstructured":"Michael Kampffmeyer , Arnt B\u00c3\u00ffrre Salberg, and Robert Jenssen . 2016 . Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks . Michael Kampffmeyer, Arnt B\u00c3\u00ffrre Salberg, and Robert Jenssen. 2016. Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks."},{"key":"e_1_3_2_1_12_1","volume-title":"SRN: Side-Output Residual Network for Object Symmetry Detection in the Wild.","author":"Ke Wei","year":"2017","unstructured":"Wei Ke , Jie Chen , Jianbin Jiao , Guoying Zhao , and Qixiang Ye . 2017 . SRN: Side-Output Residual Network for Object Symmetry Detection in the Wild. Wei Ke, Jie Chen, Jianbin Jiao, Guoying Zhao, and Qixiang Ye. 2017. SRN: Side-Output Residual Network for Object Symmetry Detection in the Wild."},{"key":"e_1_3_2_1_13_1","volume-title":"Adam: A method for stochastic optimization.","author":"Kingma Diederik","year":"2014","unstructured":"Diederik Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. Diederik Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization."},{"key":"e_1_3_2_1_14_1","unstructured":"Chenyu Lee Saining Xie Patrick W Gallagher Zhengyou Zhang and Zhuowen Tu. 2015. Deeply-Supervised Nets.  Chenyu Lee Saining Xie Patrick W Gallagher Zhengyou Zhang and Zhuowen Tu. 2015. Deeply-Supervised Nets."},{"key":"e_1_3_2_1_15_1","unstructured":"Guosheng Lin Anton Milan Chunhua Shen and Ian D Reid. 2017. RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation.  Guosheng Lin Anton Milan Chunhua Shen and Ian D Reid. 2017. RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs9050480"},{"key":"e_1_3_2_1_17_1","unstructured":"Yongcheng Liu Bin Fan Lingfeng Wang Jun Bai Shiming Xiang and Chunhong Pan. 2017. Semantic labeling in very high resolution images via a self-cascaded convolutional neural network.  Yongcheng Liu Bin Fan Lingfeng Wang Jun Bai Shiming Xiang and Chunhong Pan. 2017. Semantic labeling in very high resolution images via a self-cascaded convolutional neural network."},{"key":"e_1_3_2_1_18_1","volume-title":"Nikos Deligiannis, Wenrui Ding, and Adrian Munteanu.","author":"Liu Yu","year":"2017","unstructured":"Yu Liu , Duc Minh Nguyen , Nikos Deligiannis, Wenrui Ding, and Adrian Munteanu. 2017 . Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery . Yu Liu, Duc Minh Nguyen, Nikos Deligiannis, Wenrui Ding, and Adrian Munteanu. 2017. Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Jonathan Long Evan Shelhamer and Trevor Darrell. 2015. Fully convolutional networks for semantic segmentation.  Jonathan Long Evan Shelhamer and Trevor Darrell. 2015. Fully convolutional networks for semantic segmentation.","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"David G. Lowe. 1999. Object Recognition from Local Scale-Invariant Features.  David G. Lowe. 1999. Object Recognition from Local Scale-Invariant Features.","DOI":"10.1109\/ICCV.1999.790410"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Diego Marcos Michele Volpi Benjamin Kellenberger and Devis Tuia. 2018. Land cover mapping at very high resolution with rotation equivariant CNNs: Towards small yet accurate models.  Diego Marcos Michele Volpi Benjamin Kellenberger and Devis Tuia. 2018. Land cover mapping at very high resolution with rotation equivariant CNNs: Towards small yet accurate models.","DOI":"10.1016\/j.isprsjprs.2018.01.021"},{"key":"e_1_3_2_1_22_1","volume-title":"Matthew C H Lee, Mattias P Heinrich, Kazunari Misawa, Kensaku Mori, Steven Mcdonagh, Nils Y Hammerla","author":"Oktay Ozan","year":"2018","unstructured":"Ozan Oktay , Jo Schlemper , Loic Le Folgoc , Matthew C H Lee, Mattias P Heinrich, Kazunari Misawa, Kensaku Mori, Steven Mcdonagh, Nils Y Hammerla , Bernhard Kainz , et al. 2018 . Attention U-Net: Learning Where to Look for the Pancreas . Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew C H Lee, Mattias P Heinrich, Kazunari Misawa, Kensaku Mori, Steven Mcdonagh, Nils Y Hammerla, Bernhard Kainz, et al. 2018. Attention U-Net: Learning Where to Look for the Pancreas."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Claudio Persello and A Stein. 2017. Deep Fully Convolutional Networks for the Detection of Informal Settlements in VHR Images.  Claudio Persello and A Stein. 2017. Deep Fully Convolutional Networks for the Detection of Informal Settlements in VHR Images.","DOI":"10.1109\/LGRS.2017.2763738"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Olaf Ronneberger Philipp Fischer and Thomas Brox. 2015. U-Net: Convolutional Networks for Biomedical Image Segmentation.  Olaf Ronneberger Philipp Fischer and Thomas Brox. 2015. U-Net: Convolutional Networks for Biomedical Image Segmentation.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Jamie Shotton Matthew Johnson and Roberto Cipolla. 2008. Semantic texton forests for image categorization and segmentation.  Jamie Shotton Matthew Johnson and Roberto Cipolla. 2008. Semantic texton forests for image categorization and segmentation.","DOI":"10.1109\/CVPR.2008.4587503"},{"key":"e_1_3_2_1_26_1","unstructured":"Saining Xie and Zhuowen Tu. 2015. Holistically-nested edge detection.  Saining Xie and Zhuowen Tu. 2015. Holistically-nested edge detection."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Dan Xu Wanli Ouyang Xiaogang Wang and Nicu Sebe. 2018. PAD-Net: Multi-tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing.  Dan Xu Wanli Ouyang Xiaogang Wang and Nicu Sebe. 2018. PAD-Net: Multi-tasks Guided Prediction-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing.","DOI":"10.1109\/CVPR.2018.00077"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Xiwen Yao Junwei Han Gong Cheng Xueming Qian and Lei Guo. 2016. Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning.  Xiwen Yao Junwei Han Gong Cheng Xueming Qian and Lei Guo. 2016. Semantic Annotation of High-Resolution Satellite Images via Weakly Supervised Learning.","DOI":"10.1109\/TGRS.2016.2523563"},{"key":"e_1_3_2_1_29_1","unstructured":"Fisher Yu and Vladlen Koltun. 2016. Multi-Scale Context Aggregation by Dilated Convolutions.  Fisher Yu and Vladlen Koltun. 2016. Multi-Scale Context Aggregation by Dilated Convolutions."},{"key":"e_1_3_2_1_30_1","unstructured":"Hengshuang Zhao Jianping Shi Xiaojuan Qi Xiaogang Wang and Jiaya Jia. 2017. Pyramid Scene Parsing Network.  Hengshuang Zhao Jianping Shi Xiaojuan Qi Xiaogang Wang and Jiaya Jia. 2017. Pyramid Scene Parsing Network."}],"event":{"name":"ICDSC 2019: 13th International Conference on Distributed Smart Cameras","sponsor":["University of Trento"],"location":"Trento Italy","acronym":"ICDSC 2019"},"container-title":["Proceedings of the 13th International Conference on Distributed Smart Cameras"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3349801.3349819","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3349801.3349819","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:23:20Z","timestamp":1750202600000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3349801.3349819"}},"subtitle":["Pyramid Loss Reinforced Fully Convolutional Network"],"short-title":[],"issued":{"date-parts":[[2019,9,9]]},"references-count":30,"alternative-id":["10.1145\/3349801.3349819","10.1145\/3349801"],"URL":"https:\/\/doi.org\/10.1145\/3349801.3349819","relation":{},"subject":[],"published":{"date-parts":[[2019,9,9]]},"assertion":[{"value":"2019-09-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}