Pith Number
pith:Y7LUOHWX
pith:2017:Y7LUOHWXENNM6USOOJWVBSNEWJ
not attested
not anchored
not stored
refs pending
ClusterNet: Detecting Small Objects in Large Scenes by Exploiting Spatio-Temporal Information
arxiv:1704.02694 v2 · 2017-04-10 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{Y7LUOHWXENNM6USOOJWVBSNEWJ}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
· sign in to
claim
4
Citations
5
Replications
✓
Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-05-18T00:28:56.028274Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c7d7471ed7235acf524e726d50c9a4b267eb1211c5a648bfb310d8120ddbc9ce
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/Y7LUOHWXENNM6USOOJWVBSNEWJ \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: c7d7471ed7235acf524e726d50c9a4b267eb1211c5a648bfb310d8120ddbc9ce
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "23b3f6132a9abbee7643b3c56f3e084ca104e5dc2163be88855d98be8368299e",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2017-04-10T03:44:13Z",
"title_canon_sha256": "1d87e09668ea98dbdd092c3d36bab7f0f7d0d8cb9e1ac50ef850d0e9d06c41eb"
},
"schema_version": "1.0",
"source": {
"id": "1704.02694",
"kind": "arxiv",
"version": 2
}
}