ImageNet: A large-scale hierarchical image database (with 5 co-authors)
4 korrents from this paper
In plain words
A new image database organizes 3.2 million clean pictures under thousands of word categories from a big dictionary of meanings, far larger and more accurate than earlier image sets. That scale and structure give researchers a shared resource for object recognition, image sorting, and automatic grouping. It is a dataset release that describes gathering pictures with paid online workers and shows three simple uses.
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Near this, by wording
- He, Zhang, Ren & Sun, "Deep Residual Learning for Image Recognition" (arXiv)
- Language models are few-shot learners (with 30 co-authors)
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