融合卷积神经网络与主题模型的图像标注 下载: 843次
张蕾, 蔡明. 融合卷积神经网络与主题模型的图像标注[J]. 激光与光电子学进展, 2019, 56(20): 201004.
Lei Zhang, Ming Cai. Image Annotation Based on Convolutional Neural Network and Topic Model[J]. Laser & Optoelectronics Progress, 2019, 56(20): 201004.
[1] 彭晏飞, 宋晓男, 訾玲玲, 等. 基于卷积神经网络和改进模糊C均值的遥感图像检索[J]. 激光与光电子学进展, 2018, 55(9): 091008.
[4] Cusano C, Ciocca G, Schettini R. Image annotation using SVM[J]. Proceedings of SPIE, 2003, 5301: 330-338.
[5] Blei[\s]{1}DM,[\s]{1}Jordan[\s]{1}MI.[\s]{1}Modeling[\s]{1}annotated[\s]{1}data[C]∥Proceedings[\s]{1}of[\s]{1}the[\s]{1}26th[\s]{1}annual[\s]{1}international[\s]{1}ACM[\s]{1}SIGIR[\s]{1}conference[\s]{1}on[\s]{1}Research[\s]{1}and[\s]{1}development[\s]{1}in[\s]{1}information[\s]{1}retrieval,[\s]{1}July[\s]{1}28-August[\s]{1}1,[\s]{1}2003,[\s]{1}Toronto,[\s]{1}Canada.[\s]{1}New[\s]{1}York:[\s]{1}ACM,[\s]{1}2003:[\s]{1}127-[\s]{1}134.[\s]{1}
[7] GuillauminM,[\s]{1}MensinkT,[\s]{1}VerbeekJ,[\s]{1}et[\s]{1}al.[\s]{1}TagProp:[\s]{1}discriminative[\s]{1}metric[\s]{1}learning[\s]{1}in[\s]{1}nearest[\s]{1}neighbor[\s]{1}models[\s]{1}for[\s]{1}image[\s]{1}auto-annotation[C]∥2009[\s]{1}IEEE[\s]{1}12th[\s]{1}International[\s]{1}Conference[\s]{1}on[\s]{1}Computer[\s]{1}Vision,[\s]{1}September[\s]{1}29-October[\s]{1}2,[\s]{1}2009,[\s]{1}Kyoto,[\s]{1}Japan.[\s]{1}New[\s]{1}York:[\s]{1}IEEE,[\s]{1}2009:[\s]{1}309-[\s]{1}316.[\s]{1}
[9] 郭呈呈, 于凤芹, 陈莹. 基于卷积神经网络特征和改进超像素匹配的图像语义分割[J]. 激光与光电子学进展, 2018, 55(8): 081005.
[11] He[\s]{1}KM,[\s]{1}Zhang[\s]{1}XY,[\s]{1}Ren[\s]{1}SQ,[\s]{1}et[\s]{1}al.[\s]{1}Deep[\s]{1}residual[\s]{1}learning[\s]{1}for[\s]{1}image[\s]{1}recognition[C]∥2016[\s]{1}IEEE[\s]{1}Conference[\s]{1}on[\s]{1}Computer[\s]{1}Vision[\s]{1}and[\s]{1}Pattern[\s]{1}Recognition[\s]{1}(CVPR),[\s]{1}June[\s]{1}27-30,[\s]{1}2016,[\s]{1}Las[\s]{1}Vegas,[\s]{1}NV,[\s]{1}USA.[\s]{1}New[\s]{1}York:[\s]{1}IEEE,[\s]{1}2016:[\s]{1}770-[\s]{1}778.[\s]{1}
[12] Murthy[\s]{1}VN,[\s]{1}MajiS,[\s]{1}ManmathaR.[\s]{1}Automatic[\s]{1}image[\s]{1}annotation[\s]{1}using[\s]{1}deep[\s]{1}learning[\s]{1}representations[C]∥Proceedings[\s]{1}of[\s]{1}the[\s]{1}5th[\s]{1}ACM[\s]{1}on[\s]{1}International[\s]{1}Conference[\s]{1}on[\s]{1}Multimedia[\s]{1}Retrieval,[\s]{1}June[\s]{1}23-26,[\s]{1}2015,[\s]{1}Shanghai,[\s]{1}China.[\s]{1}New[\s]{1}York:[\s]{1}ACM,[\s]{1}2015:[\s]{1}603-[\s]{1}606.[\s]{1}
[13] 高耀东, 侯凌燕, 杨大利. 基于多标签学习的卷积神经网络的图像标注方法[J]. 计算机应用, 2017, 37(1): 228-232.
[14] 马永杰, 李雪燕, 宋晓凤. 基于改进深度卷积神经网络的交通标志识别[J]. 激光与光电子学进展, 2018, 55(12): 121009.
[16] 庄福振, 罗平, 何清, 等. 迁移学习研究进展[J]. 软件学报, 2015, 26(1): 26-29.
Zhuang F Z, Luo P, He Q, et al. Survey on transfer learning research[J]. Journal of Software, 2015, 26(1): 26-29.
[17] 李志欣, 郑永哲, 张灿龙, 等. 结合深度特征与多标记分类的图像语义标注[J]. 计算机辅助设计与图形学学报, 2018, 30(2): 318-326.
[18] 汪鹏, 张奥帆, 王利琴, 等. 基于迁移学习与多标签平滑策略的图像自动标注[J]. 计算机应用, 2018, 38(11): 3199-3203, 3210.
张蕾, 蔡明. 融合卷积神经网络与主题模型的图像标注[J]. 激光与光电子学进展, 2019, 56(20): 201004. Lei Zhang, Ming Cai. Image Annotation Based on Convolutional Neural Network and Topic Model[J]. Laser & Optoelectronics Progress, 2019, 56(20): 201004.