Weakly Supervised Cervical Histopathological Image Classification Using Multilayer Hidden Conditional Random Fields
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Hao Chen | Ning Xu | Le Zhang | Shouliang Qi | He Ma | Dan Xue | Chen Li | Hongzan Sun | Zhijie Hu | Liangzi He | N. Xu | Shouliang Qi | Chen Li | Hao Chen | Hongzan Sun | Le Zhang | He Ma | D. Xue | Zhijie Hu | Liang He
[1] Danielle B. Cooper,et al. Conization Of Cervix , 2019 .
[2] A. Jemal,et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries , 2018, CA: a cancer journal for clinicians.
[3] Chen Li,et al. Environmental microorganism classification using conditional random fields and deep convolutional neural networks , 2018, Pattern Recognit..
[4] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Chen Li,et al. Environmental Microorganism Classification Using Sparse Coding and Weakly Supervised Learning , 2015, EMR@ICMR.
[6] Vibhav Vineet,et al. Conditional Random Fields as Recurrent Neural Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[7] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[8] Zhipeng Luo,et al. Conditional Random Fields , 2014 .
[9] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[10] Vincent Lepetit,et al. DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Sudeep D. Thepade,et al. Image Retrieval using Texture Features extracted from GLCM, LBG and KPE , 2010 .
[12] Xiangyang Wang,et al. Robust image retrieval based on color histogram of local feature regions , 2010, Multimedia Tools and Applications.
[13] Vincent Lepetit,et al. A fast local descriptor for dense matching , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[14] A. Broggi,et al. Pedestrian Detection using Infrared images and Histograms of Oriented Gradients , 2006, 2006 IEEE Intelligent Vehicles Symposium.
[15] Martial Hebert,et al. Discriminative Random Fields , 2006, International Journal of Computer Vision.
[16] Yang Wang,et al. Contextual modeling of functional MR images with conditional random fields , 2006, IEEE Transactions on Medical Imaging.
[17] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[18] David G. Lowe,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.
[19] Miguel Á. Carreira-Perpiñán,et al. Multiscale conditional random fields for image labeling , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[20] Bernhard Schölkopf,et al. Training Invariant Support Vector Machines , 2002, Machine Learning.
[21] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[22] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[23] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[24] David G. Lowe,et al. Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[25] L Irwig,et al. Meta-analysis of Pap test accuracy. , 1995, American journal of epidemiology.
[26] Steven A. Shafer,et al. Anatomy of a color histogram , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[27] Teuvo Kohonen,et al. An introduction to neural computing , 1988, Neural Networks.
[28] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[29] J. M. Hammersley,et al. Markov fields on finite graphs and lattices , 1971 .