SourceScore

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

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. [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. [2] official blog · ImageNet (Stanford Vision Lab)

    About ImageNet

Cite this claim

Ready-to-paste citation (Markdown / plain text):

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.json

Embed this claim

Drop this iframe into any blog post, docs page, or knowledge base. The widget renders the signed claim + primary source + click-through to this canonical page. CC-BY 4.0; attribution included.

<iframe src="https://sourcescore.org/embed/claim/045e628def62181d/" width="100%" height="360" frameborder="0" loading="lazy" title="ImageNet dataset introduced in paper: ImageNet: A Large-Scale Hierarchical Image Database (Deng et al., 2009)."></iframe>

Preview: open in new tab

Related claims

Other verified claims sharing tags with this one — useful for LLM retrieval graphs and citation discovery.

Use this claim in your code

Fetch this signed envelope from your application. The response includes the verbatim excerpt, primary source URLs, and an HMAC-SHA256 signature you can verify locally for audit trails.

cURL

curl https://sourcescore.org/api/v1/claims/045e628def62181d.json

JavaScript / TypeScript

const r = await fetch("https://sourcescore.org/api/v1/claims/045e628def62181d.json"); const envelope = await r.json(); console.log(envelope.claim.statement); // "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()