Verified claim · AI-ML · 82% confidence
VGG (Very Deep Convolutional Networks) introduced in paper: Very Deep Convolutional Networks for Large-Scale Image Recognition (Simonyan & Zisserman, 2014).
Last verified 2026-06-01 · Methodology veritas-v0.1 · 9589ca28801022c9
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Structured fields
- Subject
- VGG (Very Deep Convolutional Networks)
- Predicate
introduced_in_paper- Object
- Very Deep Convolutional Networks for Large-Scale Image Recognition (Simonyan & Zisserman, 2014)
- Confidence
- 82%
- Tags
- vgg · convolutional-network · image-recognition · simonyan · zisserman · foundational · 2014
Sources (2)
[1] preprint · arXiv (Karen Simonyan, Andrew Zisserman) · 2014-09-04
Very Deep Convolutional Networks for Large-Scale Image Recognition“In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Our main contribution is a thorough evaluation of networks of increasing depth using an architecture with very small (3x3) convolution filters, which shows that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 weight layers.”
[2] docs · Hugging Face
Very Deep Convolutional Networks for Large-Scale Image Recognition (Hugging Face Papers)Hugging Face is rated by SourceScore — see its reliability →
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curl https://sourcescore.org/api/v1/claims/9589ca28801022c9.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/9589ca28801022c9.json");
const envelope = await r.json();
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// "VGG (Very Deep Convolutional Networks) introduced in paper: Very Deep Convolutional Networks for Large-Scale Image Recognition (Simonyan & Zisserman, 2014)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/9589ca28801022c9.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "VGG (Very Deep Convolutional Networks) introduced in paper: Very Deep Convolutional Networks for Large-Scale Image Recognition (Simonyan & Zisserman, 2014)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_vgg_very_deep_convolutional_networks_fact() -> dict:
"""Fetch the verified SourceScore claim for VGG (Very Deep Convolutional Networks)."""
r = httpx.get("https://sourcescore.org/api/v1/claims/9589ca28801022c9.json")
return r.json()