{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,7]],"date-time":"2024-07-07T01:26:10Z","timestamp":1720315570294},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T00:00:00Z","timestamp":1651363200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2022,5]]},"DOI":"10.1016\/j.eswa.2021.116438","type":"journal-article","created":{"date-parts":[[2021,12,31]],"date-time":"2021-12-31T10:46:16Z","timestamp":1640947576000},"page":"116438","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Pixel Voting Decoder: A novel decoder that regresses pixel relationships for segmentation"],"prefix":"10.1016","volume":"193","author":[{"given":"Pengfei","family":"Xian","sequence":"first","affiliation":[]},{"given":"Lai-Man","family":"Po","sequence":"additional","affiliation":[]},{"given":"Jingjing","family":"Xiong","sequence":"additional","affiliation":[]},{"given":"Chang","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Yuzhi","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Wing-Yin","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Weifeng","family":"Ou","sequence":"additional","affiliation":[]},{"given":"Yujia","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xiaori","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"12","key":"10.1016\/j.eswa.2021.116438_b0005","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","article-title":"Segnet: A deep convolutional encoder-decoder architecture for image segmentation","volume":"39","author":"Badrinarayanan","year":"2017","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2021.116438_b0010","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"9157","article-title":"Yolact: Real-time instance segmentation","author":"Bolya","year":"2019"},{"key":"10.1016\/j.eswa.2021.116438_b0015","unstructured":"L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille, Semantic image segmentation with deep convolutional nets and fully connected crfs, arXiv preprint arXiv:1412.7062, 2014."},{"issue":"4","key":"10.1016\/j.eswa.2021.116438_b0020","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","article-title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","volume":"40","author":"Chen","year":"2017","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2021.116438_b0025","unstructured":"Chen, Liang-Chieh, et al., Semantic image segmentation with deep convolutional nets and fully connected crfs. arXiv preprint arXiv:1412.7062 (2014)."},{"key":"10.1016\/j.eswa.2021.116438_b0030","unstructured":"Chen, Liang-Chieh, et al. Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587 (2017)."},{"key":"10.1016\/j.eswa.2021.116438_b0035","doi-asserted-by":"crossref","unstructured":"Chen, Liang-Chieh, et al. Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE transactions on pattern analysis and machine intelligence 40.4 (2017): 834-848.","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"10.1016\/j.eswa.2021.116438_b0040","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"12475","article-title":"Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation","author":"Cheng","year":"2020"},{"key":"10.1016\/j.eswa.2021.116438_b0045","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","article-title":"The cityscapes dataset for semantic urban scene understanding","author":"Cordts","year":"2016"},{"key":"10.1016\/j.eswa.2021.116438_b0050","series-title":"2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"764","article-title":"Deformable convolutional networks","author":"Dai","year":"2017"},{"key":"10.1016\/j.eswa.2021.116438_b0055","unstructured":"Dumoulin, Vincent, and Francesco Visin. A guide to convolution arithmetic for deep learning. arXiv preprint arXiv:1603.07285 (2016)."},{"key":"10.1016\/j.eswa.2021.116438_b0060","first-page":"1","article-title":"A survey on instance segmentation: State of the art","author":"Hafiz","year":"2020","journal-title":"International Journal of Multimedia Information Retrieval"},{"key":"10.1016\/j.eswa.2021.116438_b0065","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.eswa.2021.116438_b0070","series-title":"Proceedings of the IEEE international conference on computer vision","article-title":"Mask r-cnn","author":"He","year":"2017"},{"key":"10.1016\/j.eswa.2021.116438_b0075","unstructured":"A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam, Mobilenets: Efficient convolutional neural networks for mobile vision applications, arXiv preprint arXiv:1704.04861, 2017."},{"key":"10.1016\/j.eswa.2021.116438_b0085","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6409","article-title":"Mask scoring r-cnn","author":"Huang","year":"2019"},{"key":"10.1016\/j.eswa.2021.116438_b0090","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"4700","article-title":"Densely connected convolutional networks","author":"Huang","year":"2017"},{"key":"10.1016\/j.eswa.2021.116438_b0100","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9404","article-title":"Panoptic segmentation","author":"Kirillov","year":"2019"},{"key":"10.1016\/j.eswa.2021.116438_b0105","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops","article-title":"Fully convolutional region proposal networks for multispectral person detection","author":"Konig","year":"2017"},{"key":"10.1016\/j.eswa.2021.116438_b0110","series-title":"Advances in neural information processing systems","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"Krizhevsky","year":"2012"},{"key":"10.1016\/j.eswa.2021.116438_b0115","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.neucom.2019.02.003","article-title":"Survey on semantic segmentation using deep learning techniques","volume":"338","author":"Lateef","year":"2019","journal-title":"Neurocomputing"},{"key":"10.1016\/j.eswa.2021.116438_b0120","series-title":"European conference on computer vision","article-title":"Microsoft coco: Common objects in context","author":"Lin","year":"2014"},{"key":"10.1016\/j.eswa.2021.116438_b0135","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"3431","article-title":"Fully convolutional networks for semantic segmentation","author":"Long","year":"2015"},{"issue":"2","key":"10.1016\/j.eswa.2021.116438_b0140","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1109\/JPROC.2016.2607121","article-title":"A critical survey of deconvolution methods for separating cell types in complex tissues","volume":"105","author":"Mohammadi","year":"2016","journal-title":"Proceedings of the IEEE"},{"key":"10.1016\/j.eswa.2021.116438_b0145","series-title":"Proceedings of the IEEE international conference on computer vision","first-page":"1520","article-title":"Learning deconvolution network for semantic segmentation","author":"Noh","year":"2015"},{"key":"10.1016\/j.eswa.2021.116438_b0150","series-title":"Proceedings of the IEEE international conference on computer vision","article-title":"Learning deconvolution network for semantic segmentation","author":"Noh","year":"2015"},{"key":"10.1016\/j.eswa.2021.116438_b0155","unstructured":"Paszke, Adam, et al. Pytorch: An imperative style, high-performance deep learning library. arXiv preprint arXiv:1912.01703 (2019)."},{"key":"10.1016\/j.eswa.2021.116438_b0160","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","article-title":"Pvnet: Pixel-wise voting network for 6dof pose estimation","author":"Peng","year":"2019"},{"key":"10.1016\/j.eswa.2021.116438_b0170","doi-asserted-by":"crossref","unstructured":"O. Ronneberger, P. Fischer, and T. Brox, U-net: Convolutional networks for biomedical image segmentation. In; International Conference on Medical image computing and computer-assisted intervention. Springer, 2015, pp. 234\u2013241.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"10.1016\/j.eswa.2021.116438_b0175","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","article-title":"Semantic segmentation via structured patch prediction, context crf and guidance crf","author":"Shen","year":"2017"},{"key":"10.1016\/j.eswa.2021.116438_b0190","unstructured":"Simonyan, Karen, and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"10.1016\/j.eswa.2021.116438_b0195","series-title":"22nd International Conference on Soft Computing. Vysok\u00e9 u\u010den\u00ed technick\u00e9 v Brn\u011b","article-title":"Refined Max-Pooling and Unpooling Layers for Deep Convolutional Neural Networks Mendel 2016","author":"\u0160krab\u00e1nek","year":"2016"},{"key":"10.1016\/j.eswa.2021.116438_b0200","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","first-page":"1","article-title":"Going deeper with convolutions","author":"Szegedy","year":"2015"},{"key":"10.1016\/j.eswa.2021.116438_b0215","series-title":"Solo: Segmenting objects by locations European Conference on Computer Vision","first-page":"649","author":"Wang","year":"2020"},{"key":"10.1016\/j.eswa.2021.116438_b0225","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"12193","article-title":"Polarmask: Single shot instance segmentation with polar representation","author":"Xie","year":"2020"},{"key":"10.1016\/j.eswa.2021.116438_b0230","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"8818","article-title":"Upsnet: A unified panoptic segmentation network","author":"Xiong","year":"2019"},{"key":"10.1016\/j.eswa.2021.116438_b0235","doi-asserted-by":"crossref","unstructured":"Zagoruyko S, Lerer A, Lin T Y, et al. A multipath network for object detection. arXiv preprint arXiv:1604.02135, 2016.","DOI":"10.5244\/C.30.15"},{"key":"10.1016\/j.eswa.2021.116438_b0240","series-title":"2010 IEEE Computer Society Conference on computer vision and pattern recognition","article-title":"Deconvolutional networks","author":"Zeiler","year":"2010"},{"key":"10.1016\/j.eswa.2021.116438_b0245","series-title":"2011 International Conference on Computer Vision","article-title":"Adaptive deconvolutional networks for mid and high level feature learning","author":"Zeiler","year":"2011"},{"key":"10.1016\/j.eswa.2021.116438_b0255","series-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","article-title":"Pyramid scene parsing network","author":"Zhao","year":"2017"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417421017255?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417421017255?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2023,3,12]],"date-time":"2023-03-12T05:00:25Z","timestamp":1678597225000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417421017255"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5]]},"references-count":40,"alternative-id":["S0957417421017255"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2021.116438","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2022,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Pixel Voting Decoder: A novel decoder that regresses pixel relationships for segmentation","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2021.116438","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"116438"}}