Fetching the paper…
Reading the bibliography…
Convolutional Neural Networks (CNN) are state-of-the-art models for many image classification tasks.
Solving the multiple instance problem with axis-parallel rectangles
T. G. Dietterich, R. H. Lathrop, and T. Lozano-Pérez · 1997
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
A framework for multiple-instance learning
O. Maron and T. Lozano-Pérez · 1998
Earlier work this paper cites.
Multi instance neural networks
J. Ramon and L. De Raedt · 2000
Earlier work this paper cites.
Data vs. decision fusion in the category theory framework
M. M. Kokar, J. A. Tomasik, and J. Weyman · 2001
Earlier work this paper cites.
Quantification of histochemical staining by color deconvolution
A. C. Ruifrok and D. A. Johnston · 2001
Earlier work this paper cites.
Em-dd: An improved multiple-instance learning technique
Q. Zhang and S. A. Goldman · 2001
Earlier work this paper cites.
Support vector machines for multiple-instance learning
S. Andrews, I. Tsochantaridis, and T. Hofmann · 2002
Earlier work this paper cites.
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
T. Ojala, M. Pietikainen, and T. Maenpaa · 2002
Earlier work this paper cites.
Neural networks for multi-instance learning
Z.-H. Zhou and M.-L. Zhang · 2002
Earlier work this paper cites.
A two-level learning method for generalized multi-instance problems
N. Weidmann, E. Frank, and B. Pfahringer · 2003
Earlier work this paper cites.
A bayesian hierarchical model for learning natural scene categories
L. Fei-Fei and P. Perona · 2005
Earlier work this paper cites.
Clarifying the diffuse gliomas an update on the morphologic features and markers that discriminate oligodendroglioma from astrocytoma
M. Gupta, A. Djalilvand, and D. J. Brat · 2005
Earlier work this paper cites.
Multiple instance boosting for object detection
C. Zhang, J. C. Platt, and P. A. Viola · 2005
Earlier work this paper cites.
Pattern recognition and machine learning
C. M. Bishop et al · 2006
Earlier work this paper cites.
Evaluating bag-of-visual-words representations in scene classification
J. Yang, Y.-G. Jiang, A. G. Hauptmann, and C.-W. Ngo · 2007
Earlier work this paper cites.
Diagnosis of malignant glioma: role of neuropathology
D. J. Brat, R. A. Prayson, T. C. Ryken, and J. J. Olson · 2008
Earlier work this paper cites.
Weakly supervised discriminative localization and classification: a joint learning process
M. H. Nguyen, L. Torresani, F. De La Torre, and C. Rother · 2009
Cited alongside, same era.
Color graphs for automated cancer diagnosis and grading
D. Altunbay, C. Cigir, C. Sokmensuer, and C. Gunduz-Demir · 2010
Cited alongside, same era.
A review of multi-instance learning assumptions
J. Foulds and E. Frank · 2010
Cited alongside, same era.
Gaussian processes multiple instance learning
M. Kim and F. Torre · 2010
Cited alongside, same era.
Libsvm: a library for support vector machines
C.-C. Chang and C.-J. Lin · 2011
Cited alongside, same era.
Integrated morphologic analysis for the identification and characterization of disease subtypes
L. A. Cooper, J. Kong, D. A. Gutman, F. Wang, J. Gao, C. Appin, S. Cholleti, T. Pan, A. Sharma, L. Scarpace, et al · 2012
Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks
A. Cruz-Roa, A. Basavanhally, F. González, H. Gilmore, M. Feldman, S. Ganesan, N. Shih, J. Tomaszewski, and A. Madabhushi · 2014
Later among the works it cites.
Improving human action recognition using score distribution and ranking
M. Hoai and A. Zisserman · 2014
Later among the works it cites.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
Later among the works it cites.
Large-scale video classification with convolutional neural networks
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei · 2014
Later among the works it cites.
Fully convolutional multi-class multiple instance learning
D. Pathak, E. Shelhamer, J. Long, and T. Darrell · 2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
An efficient parallel neural network-based multi-instance learning algorithm
C. H. Li, I. Gondra, and L. Liu · 2012
Cited alongside, same era.
Multiple instance classification: Review, taxonomy and comparative study
J. Amores · 2013
Cited alongside, same era.
Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
Cited alongside, same era.
Multi-instance multi-label image classification: A neural approach
Z. Chen, Z. Chi, H. Fu, and D. Feng · 2013
Cited alongside, same era.
Mitosis detection in breast cancer histology images with deep neural networks
D. C. Cireşan, A. Giusti, L. M. Gambardella, and J. Schmidhuber · 2013
Cited alongside, same era.
P. O. Pinheiro and R. Collobert · 2014
Later among the works it cites.
2d view aggregation for lymph node detection using a shallow hierarchy of linear classifiers
A. Seff, L. Lu, K. M. Cherry, H. R. Roth, J. Liu, S. Wang, J. Hoffman, E. B. Turkbey, and R. M. Summers · 2014
Later among the works it cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Later among the works it cites.
Deep learning of feature representation with multiple instance learning for medical image analysis
Y. Xu, T. Mo, Q. Feng, P. Zhong, M. Lai, E. I. Chang, et al · 2014
Later among the works it cites.
Weakly supervised histopathology cancer image segmentation and classification
Y. Xu, J.-Y. Zhu, I. Eric, C. Chang, M. Lai, and Z. Tu · 2014
Later among the works it cites.
Classification of histology sections via multispectral convolutional sparse coding
Y. Zhou, H. Chang, K. Barner, P. Spellman, and B. Parvin · 2014
Later among the works it cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Closest in time.
Automated discrimination of lower and higher grade gliomas based on histopathological image analysis
H. S. Mousavi, V. Monga, G. Rao, and A. U. Rao · 2015
Closest in time.
Weakly-and semi-supervised learning of a dcnn for semantic image segmentation
G. Papandreou, L.-C. Chen, K. Murphy, and A. L. Yuille · 2015
Closest in time.
Dfdl: Discriminative feature-oriented dictionary learning for histopathological image classification
T. H. Vu, H. S. Mousavi, V. Monga, U. Rao, and G. Rao · 2015
Closest in time.
Deep convolutional activation features for large scale brain tumor histopathology image classification and segmentation
Y. Xu, Z. Jia, Y. Ai, F. Zhang, M. Lai, E. I. Chang, et al · 2015
Closest in time.