A visual embedding for the unsupervised extraction of abstract semantics

Author:

Garcia-Gasulla D.,Ayguadé E.,Labarta J.,Béjar J.,Cortés U.,Suzumura T.,Chen R.

Funder

IBM/BSC Deep Learning Center

Spanish Ministry of Science and Technology

Generalitat de Catalunya

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Experimental and Cognitive Psychology,Software

Reference18 articles.

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3. Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., & Darrell, T. (2013). Decaf: A deep convolutional activation feature for generic visual recognition. arXiv preprint arXiv:1310.1531.

4. Frome, A., Corrado, G. S., Shlens, J., Bengio, S., Dean, J., & Mikolov, T. (2013). Devise: A deep visual-semantic embedding model. In Advances in neural information processing systems (pp. 2121–2129).

5. He, K., Zhang, X., Ren, S., & Sun, J. (2015). Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In Proceedings of the IEEE international conference on computer vision (pp. 1026–1034).

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