{“状态”:“确定”,“消息类型”:“工作”,“信息版本”:“1.0.0”,“邮件”:{“索引”:{“日期部分”:[[2024,2,1]],“日期时间”:“2024-02-01T02:54:51Z”,“时间戳”:1706756091416},“参考计数”:50,“发布者”:“Elsevier BV”,“许可证”:[{“开始”:}“日期部分“:[2022,1,1]]”,“日期-时间”:”2022-01-01T00:00Z,“timestamp”:1640995200000},“content-version”:“tdm”,“delay-in-days”:0,“URL”:“https:\/\/www.elsevier.com/tdm\/userlicense\/1.0\/”},{“start”:{“date-parts”:[2022,1,1]],“date-time”:“2022-01-01T00:00:00Z”,“timestamp”:1640995200000},“content-version”:“stm-asf”,“delay-in-days”:“0,”URL“https:\\/doi.org\/10.15223\/policy-017”},{“开始”:{“日期部分”:[2022,1,1]],“日期时间”:“2022-01-01T00:00:00Z”,“timestamp”:1640995200000},“content-version”:“stm-asf”,“delay-in-days”:0,“URL”:“https:\/\/doi.org\/10.15223\/policy-037”},{“start”:{“date-parts”:[2022,1,1]],“date-time”:“2022-01-01T00:00:00Z”,“timetamp”:6409520000},doi.org \/10.15223 \/policy-012“},{”开始“:{”日期部分“:[2022,1,1]],“date-time”:“2022-01-01T00:00:00Z”,“timestamp”:1640995200000},“content-version”:“stm-asf”,“delay-in-days”:0,“URL”:“https:\/\/doi.org\/10.15223\/policy-029”},{“start”:{“date-parts”:[2022,1,1]],“date-pame:”2022-01-001T00:00Z“timestamport”:1640.959520000},-days“:0,”URL“:”https:\/\/doi.org\/10.15223\/policy-004“}],“资助者”:[{“DOI”:“10.13039\/50101100001809”,“名称”:“国家自然科学基金会”,“DOI断言者”:“出版商”,“奖项”:[“61562086”,“U1803261”]}],“内容域”:{“域”:[“elsevier.com”,“sciencedirect.com”],“交叉标记限制”:true},“短容器标题”:[“视觉传达与图像表达杂志”],“已发布的印刷品”:{“日期部分”:[[2022,1]}},“DOI”:“10.1016\/j.jvcir.20211.103414”,“类型”:“期刊文章”,“已创建”:{“日期部分”:[[2021,12,13]],“日期时间”:“2021-12-13T16:45:59Z”,“时间戳”:1639413959000},“页面”:“103414”,“更新策略”:“http:\/\/dx.DOI.org/10.1016\/elsevier_cm_policy”,“源”:“Crossref”,”由计数“:3,”标题“引用:[“用于细粒度视觉分类的跨层递进注意双线性融合方法”],“前缀”:“10.1016”,“卷”:“82”,“作者”:[{“给定”:“朝清”,“家庭”:“王”,“序列”:“第一”,“从属”:[]},{“给出”:“玉荣”,“家族”:“钱”,“顺序”:“附加”,“隶属”:[]},}“给定的”:“卫军”,“家人”:“龚”,“序号”:“额外”,“affiliation”:[]},{“given”:“Junjong”,“family”:“Cheng”,”sequence“:“additional”,”affiliance“:[]{,”given“:”永强“,”family“:”Wang“,”segment“:”additional“,”affaliation“:[]},”fixed“:”岳飞“,”家人“:”王“,”序列“:”附加“,”从属关系“:[[]}],“member”:“78”,“reference”:[{“issue”:“11”,“key”:”10.1 016\/j.jvcir.2021.103414_b0005“,“doi-asserted-by”:“crossref”,“first page”:“5552”,“doi”:“10.1109\/TIP.2019.2916757”,“article-title”:“CAM-RNN:基于共同关注模型的视频字幕RNN”,“volume”:”28“,“author”:“Zhao”,“year”:“2019”,“journal-title“:”IEEE Trans.Image Process.“},{”key“10.1016\/jvcir.2021.03414_b0010”,“unstructured”:“李雪龙等人,MAM-RNN:基于多层次注意模型的视频字幕RNN,载于:第二十六届国际人工智能联合会议,2017年,第2208\u20132214页。”},{“问题”:“18”,“关键”:“10.1016\/j.jvcir.2021.03414_b0015”,“doi-asserted-by”:“crossref”,“第一页”:“14613”,“doi”:“10.0007”,“article-title”:“零售产品识别中基于自我关注的破坏和构造学习细粒度图像分类方法”,“volume”:“32”,“author”:“Wang”,“year”:“2020”,“journal-title“:“Neural Compute.Appl.”},{“issue”:“5”,“key”:”10.1016\/j.jvcir.2021.103414_b0020“,”doi-asserted-by“:”crossref“,”第一页“1681”,“doi”:“10.3390\/app10051681”,“article-title”:“利用挤压和激发以及空间注意模块对生态图像中的细颗粒蝴蝶进行分类”,“volume”:“10”,“author”:“Xin”,“year”:“2020”,“journal-title“:”Appl.Sci.“},{“key”:”10.1016\/j.jvcir.2021.03414_b0025“,”doi-asserted-by“:”crossref“,”doi“:”10.3389\/fpls.2020.600854“,“文章标题”:“基于注意力机制的作物病害细粒度图像分类”,“卷”:“11”,“作者”:“Yang”,“年份”:“2020”,“期刊标题”:“Front.Plant Sci.”},{“key”:“10.1016\/j.jvcir.20211.04_4b0030”,“非结构化”:“Catherine Wah et al.,加州理工大学可持续发展学院鸟类-200-2011数据集,2011.”},{“key”:“10.1016\/j.jvcir.2021.103414_b0035”,“series-title”:“Proc.IEEE Conf.Compute.Vision and Pattern Recognition”,“article-title”:“用于精细纹理图像分类的新数据集”,“author”:“Khosla”,“year”:“2011”},{“key”:,“首页”:“554”,“文章标题”:“用于细粒度分类的三维对象表示”,“作者”:“Krause”,“年份”:“2013”},{“关键”:“10.1016\/j.jvcir.2021.03414_b0045”,“非结构化”:“Subhransu Maji等人,飞机细粒度视觉分类。ArXiv预印本ArXiv:1306.5151,2013.”}、{“键”:“1016\/j.jvcir.2021.103414~b0050”,“doi-asserted-by”:“crossref”,“unstructured”:“M.E.Nilsback,A.Zisserman,《大量类别的花卉自动分类》,载于:2008年第六届印度计算机视觉、图形和图像处理会议,2008年,第722\u2013729.页”,“doi”:“10.1109\/ICVGIP.2008.47”},{“key”:“101016\/j.jvcir.2021.103414_b0055”,“series-title”:“2015 IEEE国际计算机视觉会议(ICCV)”,“首页”:“1449”,“article-title”:“精细视觉识别的双线性CNN模型”,“author”:“Lin”,“year”:“2015”},{“key”:“10.1016\/j.jvcir.2021.03414_b0060”,“series-title”::“图像识别的因子双线性模型”,“author”:“Li”,“year”:“2017”},{“key”:“10.1016\/j.jvcir.2021.103414_b0065”,“series-title”:“欧洲计算机视觉会议论文集”,“first page”:《595》,“article-title”:《精细颗粒视觉识别的层次双线性池》,“audor”:《Yu》,“year:”2018“}”,{:“10.1016\/j.jvcir.2021.103414_b0070”,“series-title”:“欧洲计算机视觉会议”,“首页”:“834”,“article-title”:“基于零件的细粒度类别检测R-CNN”,“author”:“Zhang”,“year”:“2014”},{“key”::“使用姿态归一化深度卷积网对鸟类物种进行分类”,“作者”:“Branson”,“年份”:“2014年”,“期刊标题”:“ArXiv预印本ArXiv:1406.2952”},{“关键字”:“10.1016\/j.jvcir.2021.103414_b0080”,“series-title”:“2016 IEEE计算机视觉和模式识别会议(CVPR)”,“首页”:“770”,”文章标题“:“图像识别的深度剩余学习”,“author”:“He”,“year”:“2016”},{“key”:“10.1016\/j.jvcir.2021.103414_b0085”,“series-title”:“2017 IEEE计算机视觉与模式识别会议(CVPR)”,“first page”:”5987“,“article-title”:”Deep Neural Networks的聚合剩余变换“,”author“:”Xie“,”year“:”2017“}”,{”key“:“10.1016\/j.jvcir.2021.103414_b0090”,“series-title”:“2017 IEEE计算机视觉与模式识别会议(CVPR)”,“首页”:“2261”,“article-title”:“密集连接卷积网络”,“author”:“Huang”,“year”:“2017”},{“key”::“2018 IEEE\/CVF计算机视觉与模式识别会议”,“首页”:“7132”,“文章标题”:“挤压与激励网络”,“作者”:“胡”,“年份”:“2018”},{“密钥”:“10.1016\/j.jvcir.2021.03414_b0100”,“doi-asserted-by”:“crossref”,“非结构化”:“Yang Gao等人,紧凑双线性池,in:2016 IEEE计算机视觉和模式识别会议,2016,pp.317\u2013326.”,“DOI”:“10.1109\/CVPR.2016.41”},{“key”:“101016\/j.jvcir.2021.103414_b0105”,“DOI-asserted-by”:“crossref”,“unstructured”:“Yu Gao等人,《精细图像分类的通道交互网络》,载于:《AAAI人工智能会议论文集》,第34卷,第7期,2020年,第10818\u201310825页。”,“DOI”:“10.1609\/AAAI.v34i07.6712”},{“key”:“101016\/j.jvcir.2021.103414_b0110”,“DOI-asserted-by”:“crossref”,“unstructured”:“庄培琴等人,《学习细粒度分类的注意成对交互》,载:《AAAI人工智能会议论文集》,第34卷,第7期,2020年,第13130\u201313137页。”,“DOI”:“10.1609\/AAAI.v34i07.7016”},{“key”:“101016\/j.jvcir.2021.103414_b0115”,“DOI-asserted-by”:“crossref”,“first page”::“10.1109\/TIP.2020.2973812”,“article-title”:“The Devil Is in The Channels:Mutual-Channel Loss for Fine-Grained Image Classification”,“volume”:“29”,“author”:“Chang”,“year”:“2020”,“journal-title“:”IEEE Trans.Image Process.“},{”key“:”10.1016\/j.jvcir.2021.103414_b0120“,”series-title“:“2017 IEEE计算机视觉与模式识别会议(CVPR)”,“首页”:“4476”,“文章标题”:“更仔细地看:细粒度图像识别的递归注意卷积神经网络”,“作者”:“Fu”,“年份”:“2017”},{“key”:“10.1016\/jvcir.2021.103414_b0125”,“series-title”:“2019 IEEE \/CVF计算机视觉与模式识别会议(CVPR)”,“首页”:“5012”,“文章标题”:“细节中的魔鬼:学习精细图像识别的三线性注意取样网络”,“作者”:“郑”,“年份”:“2018”},{“key”:“10.1016\/j.jvcir.2021.03414_b0130”,“series-title”:“2020 IEEE\/CVF计算机视觉与模式识别会议(CVPR)”,“首页”:“10468”,“article-title”:“用于精细视觉分类的注意卷积二叉神经树”,“author”:“Ji”,“year”:“2020”},{“key”:“10.1016\/j.jvcir.2021.03414_b0135”,“series-title”:“2019 IEEE \/CVF国际计算机视觉会议(ICCV)”,“首页”:“6599”,“文章标题”:“细颗粒图像识别的选择性稀疏采样”,“作者”:“丁”,“年份”:“2018”},{“密钥”:“10.1016\/j.jvcir.2021.103414_b0140”,“series-title”:“欧洲计算机视觉会议论文集”,“第一页”:”438“,“article-title”:“Learning to Navigate for Fine-Grained Classification”,“author”:“Yang”,“year”:“2018”},{“key”:“10.1016\/j.jvcir.2021.03414_b0145”,“series-title”:《2020 IEEE\/CVF计算机视觉与模式识别会议(CVPR)》,“首页”:“4483”,“artifle-titel”:“通过密集的基于属性的注意力进行细粒度广义零炮学习”,“author”:“Huynh”,“year”:“2020”},{“issue”:“6”,“key”:“10.1016\/j.jvcir.2021.03414_b0150”,“doi-asserted-by”:“crossref”,“first page”:《2868》,“doi”:“101109\/TIP.2017.2688133”,《article-title》:“精细图像检索的选择性卷积描述符聚合”,“卷”:“26”,“作者”:“魏”,“年份”:“2017”,“日志标题”:“IEEE Trans.Image Process.”},{“key”:“10.1016\/j.jvcir.2021.103414_b0155”,“doi-asserted-by”:“crossref”,“非结构化”:“张传毅等人,网络监督下的精细视觉分类软更新训练网络,载《AAAI人工智能会议论文集》,第34卷,第7期,2020年,第12781\u201312788页。”,“DOI”:“10.1609\/AAAI.v34i07.6973”},{“issue”:“1”,“key”:“101016\/j.jvcir.2021.03414_b0160”,“DOI-asserted-by”:“crossref”,“first page”:“20”,“DOI”:“10.1016\/016-2236(92)90344-8”,“article-title”:“感知和行动的独立视觉路径”,“volume”:”15“,“author”:“Goodale”,”year“:”1992“,”journal-title“:”Trends Neurosci.“},{“key”:I“:”10.1109\/提示.2020.2996736“,“article-title”:“精细颗粒识别的双模渐进式掩模注意事项”,“volume”:“29”,“author”:“Song”,“year”:“2020”,“journal-title“:”IEEE Trans.Image Process.“},{“key”:”10.1016\/j.jvcir.2021.03414_b0170“,”doi-asserted-by“:”crossref“,”unstructured“:“孙晓晓等人,《利用对抗性判别神经网络从网络数据中学习精细分类》,载《AAAI人工智能会议论文集》,第33卷,2019年第1期,第273\u2013280页。”,“DOI”:“10.1609\/AAAI.v33i01.3301273”},{“key”:“101016\/j.jvcir.2021.103414_b0175”,“首页”:“153”,“article-title”:“通过Jigsaw补丁的渐进多粒度训练进行精细视觉分类”,“author”:“Du”,“year”:“2020”,“journal-title“:”ECCV(20)“},{“key”:“10.1016\/jvcir.2021.103414_b0180”,“series-title”:”2018 IEEE\/CVF计算机视觉与模式识别研讨会(CVPRW)“,“first page”:”791“,“article-title”:“通过累进级联残差网络实现图像超分辨率”,“author”:“Ahn”,“year”:“2018”},{“key”:“10.1016\/j.jvcir.2021.03414_b0185”,“unstructured”:“Tero Karras等人,GAN的累进增长以提高质量、稳定性和变异性,收录于:2018年国际学习代表大会。”}、{“key”:“10.1016\/j.jvcir.2021.103414_b0190”,“series-title”:“2018 IEEE\/CVF计算机视觉和模式识别研讨会(CVPRW)会议”,“首页”:“977”,“文章-标题”:“单图像超分辨率的全进进法”,“作者”:“王”,“年份”:“2018”},{“密钥”:“10.116\/j.jvcir.202.103414_b 0195”,“doi-asserted-by”:“crossref”,“first page”:“476”,“DOI”:“10.1109\/TIP.2019.2921876”,《article-title》:“Learning Rich Part Hierarchies With Progressive Attention Networks for Fine-Grained Image Recognition”,“volume”:”29“,“author”:“Zheng”,“year”:“2020”,“journal-title”:“IEEE Trans.Image Process.”},{“key”:《10.1016\/j.jvcir.2021.103414_b0200》,“series-title”:“2019 IEEE\/CFF计算机视觉与模式识别会议(CVPR)”,“第一页”:“5157”,“文章标题”:“细粒度图像识别的破坏与构建学习”,“作者”:“Chen”,“年份”:“2019”},{“密钥”:“10.1016\/j.jvcir.202110344_b0205”,“非结构化”:“Ilya Loshchilov,Frank Hutter,SGDR:带热重启的随机梯度下降,ICLR(海报),2016。”},{“key”:“10.1016\/j.jvcir.201.103414_b0210”,“series title”:“ICLR 2015:2015年国际学习表征大会”,“文章title”:“用于大规模图像识别的甚深卷积网络”,“author”:“Simonyan”,“year”:“2015”},{“issue”:“3”,“key”:“10.1016\/j.jvcir.2021.103414_b0215”,“doi-asserted-by”:“crossref”,“first page”:”211“,”doi“:”10.1007\/s11263-015-0816-y“,”article-title“:”ImageNet大规模视觉识别挑战“,”volume“:”115“,”author“:”Russakovsky“,,{“键”:“10.1016\/j.jvcir.2021.103414_b0220”,“series-title”:“ICLR 2016:2016国际学习代表大会”,“article-title”:“用指数线性单位(ELU)进行快速准确的深度网络学习”,“author”:“Clevert”,“year”:“2016”},{“key”:”10.1016\/j.jvcir.2021.103414_b25“,“first page”:4277“article-title“:“Learning Deep Bilinear Transformation for Fine-Grained Image Representation”,“volume”:“32”,“author”:“Zheng”,“year”:“2019”,“journal-title”:“Adv.Neural Inform.Process.Syst.”},{“key”:《10.1016\/j.jvcir.2021.03414_b0230》,“doi-asserted-by”:“crossref”,“unstructured”:“王竹辉等人,基于图传播的弱监督细粒度图像分类相关学习,载《AAAI人工智能会议论文集》,第34卷,第7期,2020年,第12289\u201312296页。”,“DOI”:“10.1609\/AAAI.v34i07.6912”},{“key”:“101016\/j.jvcir.2021.103414_b0235”,“series-title”:“2019 IEEE \/CVF国际计算机视觉会议(ICCV)”,“首页”:“8330”,“文章标题”:“学习粒度特定专家的混合精细分类”,“作者”:“张”,“年份”:“2018”},{“key”:“10.1016\/j.jvcir.2021.103414_b0240”,“doi-asserted-by”:“crossref”,“非结构化”:“刘传斌等人,《过滤和蒸馏:提高区域对细粒度视觉分类的关注度》,载于:《AAAI人工智能会议论文集》,第34卷,第7期,2020年,第11555\u201311562页。”,“DOI”:“10.1609\/AAAI.v34i07.6822”},{“key”:“101016\/j.jvcir.2021.103414_b0245”,“series-title”:“2019 IEEE\/CVF国际计算机视觉会议(ICCV)”,“首页”:“8242”,“文章标题”:“细粒度视觉分类的Cross-X学习”,“作者”:“Luo”,“年份”:“2019”},{“问题”:“2”,“密钥”:“10.1016\/j.jvcir.202110103414_b0250”,“doi断言由”:“crossref”,“首页”:“336”,“doi”:“10.1007\/s11263-019-01228-7”,“文章标题”:“Grad-CAM:通过基于梯度的本地化从深度网络中进行可视化解释”,“卷”:“128”,“作者”:“Selvaraju”,“年份”:“2020”,“日志标题”:“Int.J.Compute.Vision”}],“容器标题”:[“视觉传达与图像表现杂志”],“原始标题”:[],“语言”:“en”,“链接”:[{“URL”:“https:\/\/api.elsevier.com/content\/article\/PII:S104732032002789?httpAccept=text\/xml”,“content-type”:“text\/xml”,“content-version”:“vor”,“intended-application”:“text-mining”},{“URL”:“http:\/\-api.elsever.com/content\/article \/PII:S104732021002789?httpAccess=text\/plain”:“vor”,“intended-application”:“text-mining”}],“deposed”:{“date-parts”:[[2023,3,25]],“date-time”:“2023-03-25T20:36:26Z”,“timestamp”:1679776586000},“score”:1,“resource”:{primary“:{”URL“https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S10473202102789”},”subtitle“:[],”shorttitle“:[],”issued“日期:{parts“:[[2022,1]]},”references-count“:50,“alternative-id”:[“S104732032002789”],“URL”:“http://\/dx.doi.org\/10.1016\/j.jvcir.2021.103414”,“relationship”:{},“ISSN”:[”1047-3203“],“ISSN-type”:[{“value”:“1047-2203”,“type”:“print”}],“subject”:[/],“published”:{“date-parts”:[2022,1]},”assertion“:[[{”value“Elsevier”“,”name“:”publisher“,”label“:”本文由“},{”value“维护”:“用于细粒度视觉分类的跨层递进注意双线性融合方法”,“name”:“articletitle”,“label”:“Article Title”},{“value”:“Journal of visual Communication and Image Representation”,“name”:“journaltitle”,”label“:”Journal Title“},”{“value”:“https:\/\/doi.org\/10.1016\/j.jvcir.2021.03414”,“名称”:“rticlelink”,“标签”:“CrossRef DOI link to publisher maintained version”},{“value”:“article”,“name”:“content_type”,“label”:“content-type”}