Verified claim · AI-ML · 100% confidence
ResNet (Residual Networks) introduced in paper: Deep Residual Learning for Image Recognition (He et al., 2015).
Last verified 2026-05-16 · Methodology veritas-v0.1 · 4f55f77c4bfb316e
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Structured fields
- Subject
- ResNet (Residual Networks)
- Predicate
introduced_in_paper- Object
- Deep Residual Learning for Image Recognition (He et al., 2015)
- Confidence
- 100%
- Tags
- resnet · foundational · vision · he · 2015 · microsoft · cvpr
Sources (2)
[1] preprint · arXiv (He, Zhang, Ren, Sun) · 2015-12-10
Deep Residual Learning for Image Recognition“We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously.”
[2] peer reviewed · IEEE / Computer Vision Foundation · 2016-06-30
Deep Residual Learning (CVPR 2016 proceedings)
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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.
What is the evidence for "ResNet (Residual Networks) introduced in paper: Deep Residual Learning for Image Recognition (He et al., 2015)."?
Evidence comes from 2 primary sources: arXiv (He, Zhang, Ren, Sun), IEEE / Computer Vision Foundation. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/4f55f77c4bfb316e.json includes an HMAC-SHA256 signature for audit verification.
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// "ResNet (Residual Networks) introduced in paper: Deep Residual Learning for Image Recognition (He et al., 2015)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/4f55f77c4bfb316e.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "ResNet (Residual Networks) introduced in paper: Deep Residual Learning for Image Recognition (He et al., 2015)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_resnet_residual_networks_fact() -> dict:
"""Fetch the verified SourceScore claim for ResNet (Residual Networks)."""
r = httpx.get("https://sourcescore.org/api/v1/claims/4f55f77c4bfb316e.json")
return r.json()