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Despite the recent advances in automatically describing image contents, their applications have been mostly limited to image caption datasets containing natural images (e.g., Flickr 30k, MSCOCO).
Developing optimal search strategies for detecting clinically sound studies in medline
R. B. Haynes, N. Wilczynski, K. A. McKibbon, C. J. Walker, and J. C. Sinclair · 1994
Earlier work this paper cites.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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Bleu: a method for automatic evaluation of machine translation
K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu · 2002
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Visualizing data using t-sne
L. Van der Maaten and G. Hinton · 2008
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Natural language processing with Python
S. Bird, E. Klein, and E. Loper · 2009
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Trec genomics special issue overview
W. Hersh and E. Voorhees · 2009
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Every picture tells a story: Generating sentences from images
A. Farhadi, M. Hejrati, M. A. Sadeghi, P. Young, C. Rashtchian, J. Hockenmaier, and D. Forsyth · 2010
Earlier work this paper cites.
How many words is a picture worth? automatic caption generation for news images
Y. Feng and M. Lapata · 2010
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X-ray categorization and retrieval on the organ and pathology level, using patch-based visual words
U. Avni, H. Greenspan, E. Konen, M. Sharon, and J. Goldberger · 2011
Earlier work this paper cites.
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Earlier work this paper cites.
Improving information retrieval using medical subject headings concepts: a test case on rare and chronic diseases
S. J. Darmoni, L. F. Soualmia, C. Letord, M.-C. Jaulent, N. Griffon, B. Thirion, and A. Névéol · 2012
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Improving neural networks by preventing co-adaptation of feature detectors
G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. R. Salakhutdinov · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Generating sequences with recurrent neural networks
A. Graves · 2013
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Speech recognition with deep recurrent neural networks
A. Graves, A.-r. Mohamed, and G. Hinton · 2013
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Framing image description as a ranking task: Data, models and evaluation metrics
M. Hodosh, P. Young, and J. Hockenmaier · 2013
Earlier work this paper cites.
Babytalk: Understanding and generating simple image descriptions
G. Kulkarni, V. Premraj, V. Ordonez, S. Dhar, S. Li, Y. Choi, A. C. Berg, and T. Berg · 2013
Earlier work this paper cites.
Fast and exact: Admm-based discriminative shape segmentation with loopy part models
H. Boussaid and I. Kokkinos · 2014
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio · 2014
Earlier work this paper cites.
Empirical evaluation of gated recurrent neural networks on sequence modeling
J. Chung, C. Gulcehre, K. Cho, and Y. Bengio · 2014
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Evaluation of scan-line optimization for 3d medical image registration
S. Hermann · 2014
Cited alongside, same era.
Opinion mining with deep recurrent neural networks
O. Irsoy and C. Cardie · 2014
Cited alongside, same era.
Automatic tuberculosis screening using chest radiographs
S. Jaeger, A. Karargyris, S. Candemir, L. Folio, J. Siegelman, F. Callaghan, Z. Xue, K. Palaniappan, R. K. Singh, S. Antani, et al · 2014
Cited alongside, same era.
Joint summarization of large-scale collections of web images and videos for storyline reconstruction
G. Kim, L. Sigal, and E. P. Xing · 2014
Cited alongside, same era.
Patch-based evaluation of image segmentation
C. Ledig, W. Shi, W. Bai, and D. Rueckert · 2014
Cited alongside, same era.
Network in network
M. Lin, Q. Chen, and S. Yan · 2014
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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An empirical exploration of recurrent network architectures
R. Jozefowicz, W. Zaremba, and I. Sutskever · 2015
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Deep visual-semantic alignments for generating image descriptions
A. Karpathy and L. Fei-Fei · 2015
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Visualizing and understanding recurrent networks
A. Karpathy, J. Johnson, and F.-F. Li · 2015
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Joint photo stream and blog post summarization and exploration
G. Kim, S. Moon, and L. Sigal · 2015
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Cited alongside, same era.
Fully automated non-rigid segmentation with distance regularized level set evolution initialized and constrained by deep-structured inference
T. A. Ngo and G. Carneiro · 2014
Cited alongside, same era.
Joint coupled-feature representation and coupled boosting for ad diagnosis
Y. Shi, H.-I. Suk, Y. Gao, and D. Shen · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Grounded compositional semantics for finding and describing images with sentences
R. Socher, A. Karpathy, Q. V. Le, C. D. Manning, and A. Y. Ng · 2014
Cited alongside, same era.
Iterative multilevel mrf leveraging context and voxel information for brain tumour segmentation in mri
N. Subbanna, D. Precup, and T. Arbel · 2014
Cited alongside, same era.
G. Kim, S. Moon, and L. Sigal · 2015
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Unifying visual-semantic embeddings with multimodal neural language models
R. Kiros, R. Salakhutdinov, and R. S. Zemel · 2015
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Associating neural word embeddings with deep image representations using fisher vectors
B. Klein, G. Lev, G. Sadeh, and L. Wolf · 2015
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Addressing the rare word problem in neural machine translation
M.-T. Luong, I. Sutskever, Q. V. Le, O. Vinyals, and W. Zaremba · 2015
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Explain images with multimodal recurrent neural networks
J. Mao, W. Xu, Y. Yang, J. Wang, and A. L. Yuille · 2015
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A novel multiple-instance learning-based approach to computer-aided detection of tuberculosis on chest x-rays
J. Melendez, B. van Ginneken, P. Maduskar, R. H. Philipsen, K. Reither, M. Breuninger, I. M. Adetifa, R. Maane, H. Ayles, C. Sanchez, et al · 2015
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Image segmentation in twenty questions
C. Rupprecht, L. Peter, and N. Navab · 2015
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Interleaved text/image deep mining on a very large-scale radiology database
H.-C. Shin, L. Lu, L. Kim, A. Seff, J. Yao, and R. M. Summers · 2015
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Learning the correlation between images and disease labels using ambiguous learning
T. Syeda-Mahmood, R. Kumar, and C. Compas · 2015
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
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Sequence to sequence–video to text
S. Venugopalan, M. Rohrbach, J. Donahue, R. Mooney, T. Darrell, and K. Saenko · 2015
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Show and tell: A neural image caption generator
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan · 2015
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Show, attend and tell: Neural image caption generation with visual attention
K. Xu, J. Ba, R. Kiros, A. Courville, R. Salakhutdinov, R. Zemel, and Y. Bengio · 2015
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Chest x-ray image view classification
Z. Xue, D. You, S. Candemir, S. Jaeger, S. Antani, L. R. Long, and G. R. Thoma · 2015
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Describing videos by exploiting temporal structure
L. Yao, A. Torabi, K. Cho, N. Ballas, C. Pal, H. Larochelle, and A. Courville · 2015
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Interleaved text/image deep mining on a large-scale radiology database for automated image interpretation
H.-C. Shin, L. Lu, L. Kim, A. Seff, J. Yao, and R. M. Summers · 2016
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