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The challenge of learning a new concept, object, or a new medical disease recognition without receiving any examples beforehand is called Zero-Shot Learning (ZSL).
Distributional structure, DOI: https://doi.org/10.1080/00437956.1954.11659520 (1954)
Harris, Z. S · 1954
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Term-weighting approaches in automatic text retrieval
Salton, G. & Buckley, C · 1988
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Wordnet: a lexical database for english
Miller, G. A · 1995
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Learning from one example through shared densities on transforms
Miller, E. G., Matsakis, N. E. & Viola, P. A · 2000
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A generalized representer theorem
Schölkopf, B., Herbrich, R. & Smola, A. J · 2001
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On kernel-target alignment
Cristianini, N., Shawe-Taylor, J., Elisseeff, A. & Kandola, J. S · 2002
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Distinctive image features from scale-invariant keypoints
Lowe, D. G · 2004
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Cross-generalization: Learning novel classes from a single example by feature replacement
Bart, E. & Ullman, S · 2005
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Large margin methods for structured and interdependent output variables
Tsochantaridis, I., Joachims, T., Hofmann, T. & Altun, Y · 2005
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Shared features for multiclass object detection (Springer, 2006)
Torralba, A., Murphy, K. P. & Freeman, W. T · 2006
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One-shot learning of object categories
Fei-Fei, L., Fergus, R. & Perona, P · 2006
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A kernel method for the two-sample-problem
Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B. & Smola, A. J · 2007
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Representing shape with a spatial pyramid kernel
Bosch, A., Zisserman, A. & Munoz, X · 2007
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Matching local self-similarities across images and videos
Shechtman, E. & Irani, M · 2007
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Speeded-up robust features (surf)
Bay, H., Ess, A., Tuytelaars, T. & Van Gool, L · 2008
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Object detection and localization system based on neural networks for robo-pong
Sabzevari, R., Shahri, A., Fasih, A. R., Masoumzadeh, S. & Rezaei Ghahroudi, M · 2008
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Describing objects by their attributes
Farhadi, A., Endres, I., Hoiem, D. & Forsyth, D · 2009
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Learning to detect unseen object classes by between-class attribute transfer
Lampert, C. H., Nickisch, H. & Harmeling, S · 2009
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Zero-shot learning with semantic output codes
Palatucci, M., Pomerleau, D., Hinton, G. E. & Mitchell, T. M · 2009
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Ranking with ordered weighted pairwise classification
Usunier, N., Buffoni, D. & Gallinari, P · 2009
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Imagenet: A large-scale hierarchical image database
Deng, J. et al · 2009
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Clueweb09 data set (2009)
Callan, J., Hoy, M., Yoo, C. & Zhao, L · 2009
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Attribute-based transfer learning for object categorization with zero/one training example
Yu, X. & Aloimonos, Y · 2010
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What helps where–and why? semantic relatedness for knowledge transfer
Rohrbach, M., Stark, M., Szarvas, G., Gurevych, I. & Schiele, B · 2010
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Large scale image annotation: learning to rank with joint word-image embeddings
Weston, J., Bengio, S. & Usunier, N · 2010
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Hubs in space: Popular nearest neighbors in high-dimensional data
Radovanović, M., Nanopoulos, A. & Ivanović, M · 2010
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One shot learning of simple visual concepts
Lake, B., Salakhutdinov, R., Gross, J. & Tenenbaum, J · 2011
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The caltech-ucsd birds-200-2011 dataset
Wah, C., Branson, S., Welinder, P., Perona, P. & Belongie, S · 2011
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Evaluating knowledge transfer and zero-shot learning in a large-scale setting
Rohrbach, M., Stark, M. & Schiele, B · 2011
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Relative attributes
Parikh, D. & Grauman, K · 2011
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English gigaword fifth edition, linguistic data consortium
Parker, R., Graff, D., Kong, J., Chen, K. & Maeda, K · 2011
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Learning with hierarchical-deep models
Salakhutdinov, R., Tenenbaum, J. B. & Torralba, A · 2012
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Augmented attribute representations
Sharmanska, V., Quadrianto, N. & Lampert, C. H · 2012
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Sun attribute database: Discovering, annotating, and recognizing scene attributes
Patterson, G. & Hays, J · 2012
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Online incremental attribute-based zero-shot learning
Kankuekul, P., Kawewong, A., Tangruamsub, S. & Hasegawa, O · 2012
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Machine learning: a probabilistic perspective (MIT press, 2012)
Murphy, K. P · 2012
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I. & Hinton, G. E · 2012
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Attribute-based classification for zero-shot visual object categorization
Lampert, C. H., Nickisch, H. & Harmeling, S · 2013
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Label-embedding for attribute-based classification
Akata, Z., Perronnin, F., Harchaoui, Z. & Schmid, C · 2013
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Devise: A deep visual-semantic embedding model
Frome, A. et al · 2013
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Zero-shot learning by convex combination of semantic embeddings
Norouzi, M. et al · 2013
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Transfer learning in a transductive setting
Rohrbach, M., Ebert, S. & Schiele, B · 2013
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Write a classifier: Zero-shot learning using purely textual descriptions
Elhoseiny, M., Saleh, B. & Elgammal, A · 2013
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A unified probabilistic approach modeling relationships between attributes and objects
Wang, X. & Ji, Q · 2013
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Zero-shot learning through cross-modal transfer
Socher, R., Ganjoo, M., Manning, C. D. & Ng, A · 2013
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Auto-encoding variational bayes
Kingma, D. P. & Welling, M · 2013
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Distributed representations of words and phrases and their compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S. & Dean, J · 2013
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Look at the driver, look at the road: No distraction! no accident!
Rezaei, M. & Klette, R · 2014
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Zero-shot recognition with unreliable attributes
Jayaraman, D. & Grauman, K · 2014
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Large-scale object classification using label relation graphs
Deng, J. et al · 2014
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Creating a cascade of haar-like classifiers: Step by step (2014)
Rezaei, M · 2014
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A multi-view embedding space for modeling internet images, tags, and their semantics
Gong, Y., Ke, Q., Isard, M. & Lazebnik, S · 2014
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Generative adversarial nets
Goodfellow, I. et al · 2014
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Glove: Global vectors for word representation
Pennington, J., Socher, R. & Manning, C · 2014
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Very deep convolutional networks for large-scale image recognition
Simonyan, K. & Zisserman, A · 2014
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Siamese neural networks for one-shot image recognition
Koch, G., Zemel, R. & Salakhutdinov, R · 2015
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Evaluation of output embeddings for fine-grained image classification
Akata, Z., Reed, S., Walter, D., Lee, H. & Schiele, B · 2015
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Robust vehicle detection and distance estimation under challenging lighting conditions
Rezaei, M., M., T. & R., K · 2015
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Human-level concept learning through probabilistic program induction
Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B · 2015
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An embarrassingly simple approach to zero-shot learning
Romera-Paredes, B. & Torr, P · 2015
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Zero-shot learning via semantic similarity embedding
Zhang, Z. & Saligrama, V · 2015
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Unsupervised domain adaptation for zero-shot learning
Kodirov, E., Xiang, T., Fu, Z. & Gong, S · 2015
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Transductive multi-view zero-shot learning
Fu, Y., Hospedales, T. M., Xiang, T. & Gong, S · 2015
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Label-embedding for image classification
Akata, Z., Perronnin, F., Harchaoui, Z. & Schmid, C · 2015
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Unsupervised learning on neural network outputs: with application in zero-shot learning
Lu, Y · 2015
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Predicting deep zero-shot convolutional neural networks using textual descriptions
Lei Ba, J., Swersky, K., Fidler, S. & Others · 2015
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Cross-domain matching with squared-loss mutual information
Yamada, M. et al · 2015
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Generative moment matching networks
Li, Y., Swersky, K. & Zemel, R · 2015
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Learning structured output representation using deep conditional generative models
Sohn, K., Lee, H. & Yan, X · 2015
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Makhzani, A., Shlens, J., Jaitly, N., Goodfellow, I. & Frey, B · 2015
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Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection
Van Horn, G. et al · 2015
Cited alongside, same era.
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Zhu, Y. et al · 2015
Cited alongside, same era.
Going deeper with convolutions
Szegedy, C. et al · 2015
Cited alongside, same era.
Matching networks for one shot learning
Vinyals, O., Blundell, C., Lillicrap, T., Wierstra, D. & Others · 2016
Cited alongside, same era.
Improving semantic embedding consistency by metric learning for zero-shot classiffication
Bucher, M., Herbin, S. & Jurie, F · 2016
Cited alongside, same era.
Synthesized classifiers for zero-shot learning
Changpinyo, S., Chao, W.-L., Gong, B. & Sha, F · 2016
Zero-shot visual recognition using semantics-preserving adversarial embedding networks
Chen, L., Zhang, H., Xiao, J., Liu, W. & Chang, S.-F · 2018
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Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly
Xian, Y., Lampert, C. H., Schiele, B. & Akata, Z · 2018
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Deep contextualized word representations
Peters, M. E. et al · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J., Chang, M.-W., Lee, K. & Toutanova, K · 2018
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Zero-shot object detection
Bansal, A., Sikka, K., Sharma, G., Chellappa, R. & Divakaran, A · 2018
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Cited alongside, same era.
Zero-shot learning via joint latent similarity embedding
Zhang, Z. & Saligrama, V · 2016
Cited alongside, same era.
Relational knowledge transfer for zero-shot learning
Wang, D., Li, Y., Lin, Y. & Zhuang, Y · 2016
Cited alongside, same era.
Latent embeddings for zero-shot classification
Xian, Y. et al · 2016
Cited alongside, same era.
Multi-cue zero-shot learning with strong supervision
Akata, Z., Malinowski, M., Fritz, M. & Schiele, B · 2016
Cited alongside, same era.
Less is more: zero-shot learning from online textual documents with noise suppression
Qiao, R., Liu, L., Shen, C. & Van Den Hengel, A · 2016
Cited alongside, same era.
The more you know: Using knowledge graphs for image classification
Marino, K., Salakhutdinov, R. & Gupta, A · 2016
Cited alongside, same era.
Zero-shot object detection: Learning to simultaneously recognize and localize novel concepts
Rahman, S., Khan, S. & Porikli, F · 2018
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Zero-shot object detection by hybrid region embedding
Demirel, B., Cinbis, R. G. & Ikizler-Cinbis, N · 2018
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Towards affordable semantic searching: Zero-shot retrieval via dominant attributes
Long, Y., Liu, L., Shen, Y. & Shao, L · 2018
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Zero-shot sketch-image hashing
Shen, Y., Liu, L., Shen, F. & Shao, L · 2018
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Zero-shot visual imitation
Pathak, D. et al · 2018
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A generative approach to zero-shot and few-shot action recognition
Mishra, A. et al · 2018
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Scaling human-object interaction recognition through zero-shot learning
Shen, L., Yeung, S., Hoffman, J., Mori, G. & Fei-Fei, L · 2018
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Avatar-net: Multi-scale zero-shot style transfer by feature decoration
Sheng, L., Lin, Z., Shao, J. & Wang, X · 2018
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“zero-shot” super-resolution using deep internal learning
Shocher, A., Cohen, N. & Irani, M · 2018
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Improving zero-shot translation of low-resource languages
Lakew, S. M., Lotito, Q. F., Negri, M., Turchi, M. & Federico, M · 2018
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Matrix capsules with em routing
Hinton, G. E., Sabour, S. & Frosst, N · 2018
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A survey of zero-shot learning: Settings, methods, and applications
Wang, W., Zheng, V. W., Yu, H. & Miao, C · 2019
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Few-shot object detection via feature reweighting
Kang, B. et al · 2019
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Few-shot learning for dermatological disease diagnosis
Prabhu, V. U · 2019
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Generalized zero-and few-shot learning via aligned variational autoencoders
Schonfeld, E., Ebrahimi, S., Sinha, S., Darrell, T. & Akata, Z · 2019
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f-vaegan-d2: A feature generating framework for any-shot learning
Xian, Y., Sharma, S., Schiele, B. & Akata, Z · 2019
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Generalized zero-shot recognition based on visually semantic embedding
Zhu, P., Wang, H. & Saligrama, V · 2019
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Generalized zero shot learning via synthesis pseudo features
Li, C. et al · 2019
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Transductive zero-shot learning with visual structure constraint
Wan, Z. et al · 2019
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Gradient matching generative networks for zero-shot learning
Sariyildiz, M. B. & Cinbis, R. G · 2019
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Rethinking knowledge graph propagation for zero-shot learning
Kampffmeyer, M. et al · 2019
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A real-time ball detection approach using convolutional neural networks
Teimouri, M., Delavaran, M. H. & Rezaei, M · 2019
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Attentive region embedding network for zero-shot learning
Xie, G.-S. et al · 2019
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An efficient method for license plate localization using multiple statistical features in a multilayer perceptron neural network
Rezaei, M. & Isehaghi, M · 2019
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Zero-shot image classification using coupled dictionary embedding
Rostami, M. et al · 2019
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Leveraging the invariant side of generative zero-shot learning
Li, J. et al · 2019
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Dont even look once: Synthesizing features for zero-shot detection
Zhu, P., Wang, H. & Saligrama, V · 2019
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Bi-semantic reconstructing generative network for zero-shot learning
Shibing, X. & Zishu, G · 2019
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Canzsl: Cycle-consistent adversarial networks for zero-shot learning from natural language
Chen, Z., Li, J., Luo, Y., Huang, Z. & Yang, Y · 2019
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Generative dual adversarial network for generalized zero-shot learning
Huang, H., Wang, C., Yu, P. S. & Wang, C.-D · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Yang, Z. et al · 2019
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Albert: A lite bert for self-supervised learning of language representations
Lan, Z. et al · 2019
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Zero-shot emotion recognition via affective structural embedding
Zhan, C., She, D., Zhao, S., Cheng, M.-M. & Yang, J · 2019
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Zero-shot semantic segmentation
Bucher, M., Vu, T.-H., Cord, M. & Pérez, P · 2019
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Zero-shot video object segmentation via attentive graph neural networks
Wang, W., Lu, X., Shen, J., Crandall, D. J. & Shao, L · 2019
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Semantically tied paired cycle consistency for zero-shot sketch-based image retrieval
Dutta, A. & Akata, Z · 2019
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Doodle to search: Practical zero-shot sketch-based image retrieval
Dey, S., Riba, P., Dutta, A., Llados, J. & Song, Y.-Z · 2019
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Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs
Lázaro-Gredilla, M., Lin, D., Guntupalli, J. S. & George, D · 2019
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I know the relationships: Zero-shot action recognition via two-stream graph convolutional networks and knowledge graphs
Gao, J., Zhang, T. & Xu, C · 2019
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Deep zero-shot learning for scene sketch
Xie, Y., Xu, P. & Ma, Z · 2019
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Zero-shot entity linking by reading entity descriptions
Logeswaran, L. et al · 2019
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Improved zero-shot neural machine translation via ignoring spurious correlations
Gu, J., Wang, Y., Cho, K. & Li, V. O. K · 2019
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Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond
Artetxe, M. & Schwenk, H · 2019
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Autovc: Zero-shot voice style transfer with only autoencoder loss
Qian, K., Zhang, Y., Chang, S., Yang, X. & Hasegawa-Johnson, M · 2019
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Chronic eosinophilic pneumonia: A pediatric case
Rutigliano, I., Gorgoglione, S., Pacilio, A., De Meco, C. & Sacco, M. C · 2019
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Pneumonia detection using cnn based feature extraction
Varshni, D., Thakral, K., Agarwal, L., Nijhawan, R. & Mittal, A · 2019
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Covid-19 image data collection
Cohen, J. P., Morrison, P. & Dao, L · 2020
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Self-training with improved regularization for few-shot chest x-ray classification
Rajan, D., Thiagarajan, J. J., Karargyris, A. & Kashyap, S · 2020
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Momentum contrastive learning for few-shot covid-19 diagnosis from chest ct images
Chen, X., Yao, L., Zhou, T., Dong, J. & Zhang, Y · 2020
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Sensitivity of chest ct for covid-19: comparison to rt-pcr
Fang, Y. et al · 2020
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Chest ct manifestations of new coronavirus disease 2019 (covid-19): a pictorial review
Ye, Z., Zhang, Y., Wang, Y., Huang, Z. & Song, B · 2020
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Coronavirus disease 2019 (covid-19): role of chest ct in diagnosis and management
Li, Y. & Xia, L · 2020
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Lung infection quantification of covid-19 in ct images with deep learning
Shan, F. et al · 2020
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Narin, A., Kaya, C. & Pamuk, Z · 2020
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Clinical and ct features in pediatric patients with covid-19 infection: Different points from adults
Xia, W. et al · 2020
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Artificial intelligence distinguishes covid-19 from community acquired pneumonia on chest ct
Li, L. et al · 2020
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Radiological findings from 81 patients with covid-19 pneumonia in wuhan, china: a descriptive study
Shi, H. et al · 2020
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Time course of lung changes at chest ct during recovery from coronavirus disease 2019 (covid-19)
Zheng, C · 2020
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Covid-19 screening on chest x-ray images using deep learning based anomaly detection
Zhang, J., Xie, Y., Li, Y., Shen, C. & Xia, Y · 2020
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Covidx-net: A framework of deep learning classifiers to diagnose covid-19 in x-ray images
Hemdan, E. E.-D., Shouman, M. A. & Karar, M. E · 2020
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Covid-caps: A capsule network-based framework for identification of covid-19 cases from x-ray images
Afshar, P. et al · 2020
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Classification of covid-19 in chest x-ray images using detrac deep convolutional neural network
Abbas, A., Abdelsamea, M. M. & Gaber, M. M · 2020
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Detrac: Transfer learning of class decomposed medical images in convolutional neural networks
Abbas, A., Abdelsamea, M. M. & Gaber, M. M · 2020
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Unsupervised x-ray image segmentation with task driven generative adversarial networks
Zhang, Y., Miao, S., Mansi, T. & Liao, R · 2020
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