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A weakly-supervised semantic segmentation framework with a tied deconvolutional neural network is presented.
A framework for multiple-instance learning
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Support vector machines for multiple-instance learning
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A unified architecture for natural language processing: Deep neural networks with multitask learning
Collobert, R., Weston, J.: · 2008
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: · 2009
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., Manzagol, P.A.: · 2010
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The pascal visual object classes (voc) challenge
Everingham, M., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: · 2010
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Adaptive deconvolutional networks for mid and high level feature learning
Zeiler, M.D., Taylor, G.W., Fergus, R.: · 2011
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
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Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
Hinton, G., Deng, L., Yu, D., Dahl, G.E., Mohamed, A.r., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T.N., et al.: · 2012
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Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition
Dahl, G.E., Yu, D., Deng, L., Acero, A.: · 2012
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Theano: new features and speed improvements
Bastien, F., Lamblin, P., Pascanu, R., Bergstra, J., Goodfellow, I.J., Bergeron, A., Bouchard, N., Bengio, Y.: · 2012
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Automatic screening for tuberculosis in chest radiographs: a survey
Jaeger, S., Karargyris, A., Candemir, S., Siegelman, J., Folio, L., Antani, S., Thoma, G.: · 2013
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Learning phrase representations using rnn encoder–decoder for statistical machine translation
Cho, K., Gulcehre, B.v.M.C., Bahdanau, D., Schwenk, F.B.H., Bengio, Y.: · 2014
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Scalable object detection using deep neural networks
Erhan, D., Szegedy, C., Toshev, A., Anguelov, D.: · 2014
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Simultaneous detection and segmentation
Hariharan, B., Arbeláez, P., Girshick, R., Malik, J.: · 2014
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Visualizing and understanding convolutional networks
Zeiler, M.D., Fergus, R.: · 2014
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Automatic tuberculosis screening using chest radiographs
Jaeger, S., Karargyris, A., Candemir, S., Folio, L., Siegelman, J., Callaghan, F., Xue, Z., Palaniappan, K., Singh, R.K., Antani, S., et al.: · 2014
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Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration
Candemir, S., Jaeger, S., Palaniappan, K., Musco, J.P., Singh, R.K., Xue, Z., Karargyris, A., Antani, S., Thoma, G., McDonald, C.J.: · 2014
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Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Dai, J., He, K., Sun, J.: · 2015
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Weakly-and semi-supervised learning of a dcnn for semantic image segmentation
Papandreou, G., Chen, L.C., Murphy, K., Yuille, A.L.: · 2015
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From image-level to pixel-level labeling with convolutional networks
Pinheiro, P.O., Collobert, R.: · 2015
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Constrained convolutional neural networks for weakly supervised segmentation
Pathak, D., Krahenbuhl, P., Darrell, T.: · 2015
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Learning transferrable knowledge for semantic segmentation with deep convolutional neural network
Hong, S., Oh, J., Han, B., Lee, H.: · 2015
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Pathak, D., Shelhamer, E., Long, J., Darrell, T.: · 2014
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Overfeat: Integrated recognition, localization and detection using convolutional networks
Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., LeCun, Y.: · 2014
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Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2015
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Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks
Bell, S., Zitnick, C.L., Bala, K., Girshick, R.: · 2015
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Is object localization for free?–weakly-supervised learning with convolutional neural networks
Oquab, M., Bottou, L., Laptev, I., Sivic, J.: · 2015
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Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., Darrell, T.: · 2015
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Decoupled deep neural network for semi-supervised semantic segmentation
Hong, S., Noh, H., Han, B.: · 2015
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Weakly supervised semantic segmentation for social images
Zhang, W., Zeng, S., Wang, D., Xue, X.: · 2015
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Semantic image segmentation with deep convolutional nets and fully connected crfs
Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: · 2015
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Hypercolumns for object segmentation and fine-grained localization
Hariharan, B., Arbeláez, P., Girshick, R., Malik, J.: · 2015
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Feedforward semantic segmentation with zoom-out features
Mostajabi, M., Yadollahpour, P., Shakhnarovich, G.: · 2015
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Learning deconvolution network for semantic segmentation
Noh, H., Hong, S., Han, B.: · 2015
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Instance-aware semantic segmentation via multi-task network cascades
Dai, J., He, K., Sun, J.: · 2015
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Learning to segment object candidates
Pinheiro, P.O., Collobert, R., Dollar, P.: · 2015
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