Art
J-GLOBAL ID:202002268582161371   Reference number:20A0429974

End-to-End Deep Image Reconstruction From Human Brain Activity

ヒト脳活動からの末端から端までの深部画像再構成【JST・京大機械翻訳】
Author (6):
Material:
Volume: 13  Page: 21  Publication year: 2019 
JST Material Number: U7036A  ISSN: 1662-5188  Document type: Article
Article type: 原著論文  Country of issue: Switzerland (CHE)  Language: ENGLISH (EN)
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Deep neural networks (DNNs) ha...
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Brain and nervous system models  ,  Central nervous system 
Reference (28):
  • Agrawal P., Stansbury D., Malik J., Gallant J. L. (2014). Pixels to Voxels: Modeling Visual Representation in the Human Brain. arXiv [Preprint] arXiv:1407.5104. Available online at: https://arxiv.org/abs/1407.5104 (accessed October 23, 2017).
  • Cichy R. M., Khosla A., Pantazis D., Torralba A., Oliva A. (2016). Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence. Sci. Rep. 6:27755. doi: 10.1038/srep27755
  • Cowen A. S., Chun M. M., Kuhl B. A. (2014). Neural portraits of perception: reconstructing face images from evoked brain activity. NeuroImage 94, 12-22. doi: 10.1016/j.neuroimage.2014.03.018
  • Deng J., Dong W., Socher R., Li L., Li K., Fei-Fei L. (2009). "ImageNet: a large-scale hierarchical image database," in 2009 IEEE Conference on Computer Vision and Pattern Recognition (Miami, FL), 248-255. doi: 10.1109/CVPR.2009.5206848
  • Dosovitskiy A., Brox T. (2016a). "Inverting visual representations with convolutional networks," in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Las Vegas, NV), 4829-4837. doi: 10.1109/CVPR.2009.5206848
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