Verified claim · AI-ML · 100% confidence
ImageNet dataset introduced in paper: ImageNet: A Large-Scale Hierarchical Image Database (Deng et al., 2009).
Last verified 2026-05-16 · Methodology veritas-v0.1 · 045e628def62181d
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Structured fields
- Subject
- ImageNet dataset
- Predicate
introduced_in_paper- Object
- ImageNet: A Large-Scale Hierarchical Image Database (Deng et al., 2009)
- Confidence
- 100%
- Tags
- imagenet · dataset · vision · foundational · fei-fei-li · 2009 · cvpr
Sources (2)
[1] peer reviewed · CVPR 2009 (Deng, Dong, Socher, Li, Li, Fei-Fei) · 2009-06-20
ImageNet: A Large-Scale Hierarchical Image Database“ImageNet is a large-scale ontology of images built upon the backbone of the WordNet structure.”
[2] official blog · ImageNet (Stanford Vision Lab)
About ImageNet
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ImageNet dataset introduced in paper: ImageNet: A Large-Scale Hierarchical Image Database (Deng et al., 2009). — SourceScore Claim 045e628def62181d (verified 2026-05-16). https://sourcescore.org/api/v1/claims/045e628def62181d.jsonEmbed this claim
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Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
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Evidence comes from 2 primary sources: CVPR 2009 (Deng, Dong, Socher, Li, Li, Fei-Fei), ImageNet (Stanford Vision Lab). Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/045e628def62181d.json includes an HMAC-SHA256 signature for audit verification.
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Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.
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// "ImageNet dataset introduced in paper: ImageNet: A Large-Scale Hierarchical Image Database (Deng et al., 2009)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/045e628def62181d.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "ImageNet dataset introduced in paper: ImageNet: A Large-Scale Hierarchical Image Database (Deng et al., 2009)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_imagenet_dataset_fact() -> dict:
"""Fetch the verified SourceScore claim for ImageNet dataset."""
r = httpx.get("https://sourcescore.org/api/v1/claims/045e628def62181d.json")
return r.json()