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Tae Joon Jun | Youngsub Eom | Dohyeun Kim | Cherry Kim | Ji-Hye Park | Hoang Minh Nguyen | Daeyoung Kim | Ji-Hye Park | Y. Eom | Cherry Kim | Dohyeun Kim | Daeyoung Kim | T. Jun
[1] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[2] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Andrew L. Maas. Rectifier Nonlinearities Improve Neural Network Acoustic Models , 2013 .
[4] Tien Yin Wong,et al. Glaucoma detection based on deep convolutional neural network , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[5] U. Rajendra Acharya,et al. Automated Diagnosis of Glaucoma Using Texture and Higher Order Spectra Features , 2011, IEEE Transactions on Information Technology in Biomedicine.
[6] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[7] Yoram Singer,et al. An Efficient Boosting Algorithm for Combining Preferences by , 2013 .
[8] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[9] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[10] M. C. Leske,et al. The Lens Opacities Classification System III , 1993 .
[11] Gretchen A. Stevens,et al. Causes of vision loss worldwide, 1990-2010: a systematic analysis. , 2013, The Lancet. Global health.
[12] Dimitris N. Metaxas,et al. Ranking Model for Facial Age Estimation , 2010, 2010 20th International Conference on Pattern Recognition.
[13] U. Rajendra Acharya,et al. Wavelet-Based Energy Features for Glaucomatous Image Classification , 2012, IEEE Transactions on Information Technology in Biomedicine.
[14] Gregory N. Hullender,et al. Learning to rank using gradient descent , 2005, ICML.
[15] Daeyoung Kim,et al. 2sRanking-CNN: A 2-stage ranking-CNN for diagnosis of glaucoma from fundus images using CAM-extracted ROI as an intermediate input , 2018, BMVC.
[16] U. Rajendra Acharya,et al. Automated Diagnosis of Glaucoma Using Digital Fundus Images , 2009, Journal of Medical Systems.
[17] László G. Nyúl,et al. Glaucoma risk index: Automated glaucoma detection from color fundus images , 2010, Medical Image Anal..
[18] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[19] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[20] Gretchen A. Stevens,et al. Global prevalence of vision impairment and blindness: magnitude and temporal trends, 1990-2010. , 2013, Ophthalmology.
[21] Tsuyoshi Murata,et al. {m , 1934, ACML.
[22] Matthew D. Zeiler. ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.
[23] Jiang Liu,et al. Integrating holistic and local deep features for glaucoma classification , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[24] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[25] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[27] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[28] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[29] Bolei Zhou,et al. Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Thore Graepel,et al. Large Margin Rank Boundaries for Ordinal Regression , 2000 .
[31] Xiaochun Cao,et al. Disc-Aware Ensemble Network for Glaucoma Screening From Fundus Image , 2018, IEEE Transactions on Medical Imaging.
[32] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[34] M. He,et al. Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs. , 2018, Ophthalmology.
[35] Tien Yin Wong,et al. ORIGA-light: An online retinal fundus image database for glaucoma analysis and research , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[36] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[37] Tin Aung,et al. Determinants of anterior chamber depth: the Singapore Chinese Eye Study. , 2012, Ophthalmology.
[38] Ravi Thomas,et al. Primary open angle glaucoma. , 1990, The National medical journal of India.
[39] S. Kingman. Glaucoma is second leading cause of blindness globally. , 2004, Bulletin of the World Health Organization.
[40] Ming Dong,et al. Deep Age Estimation: From Classification to Ranking , 2018, IEEE Transactions on Multimedia.
[41] M. C. Leske,et al. Prevalence of open-angle glaucoma among adults in the United States. , 2004, Archives of ophthalmology.
[42] Sepp Hochreiter,et al. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) , 2015, ICLR.
[43] L. Sobin,et al. TNM Classification of Malignant Tumours , 1987, UICC International Union Against Cancer.