ImageNet Large Scale Visual Recognition Challenge.¶
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., et al. (2015). ImageNet Large Scale Visual Recognition Challenge. International Journal of Computer Vision, 115(3), 211-252.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Extrapolation Beyond Sampled Regime
- The sampled regime is the training distribution — say, photographs of the thousand object classes it learned.
This sourceDocuments the thousand-class photographic training distribution that defines the sampled regime of standard image classifiers.
Supported in partVerified against the publisher's abstract
The abstract documents ILSVRC as an object-category classification benchmark of hundreds of categories and millions of images, but states neither a thousand-class training distribution nor the term 'sampled regime'.
“The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images.”
- The sampled regime is the training distribution — say, photographs of the thousand object classes it learned.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 1 of 1 citation: 1 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
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Registry ID ref:547dfb8e757d · see in the full table