Pith Number
pith:NP4ODDD3
pith:2019:NP4ODDD3MCLET35YI7ZVXTZZ3U
not attested
not anchored
not stored
refs pending
Quantifying Legibility of Indoor Spaces Using Deep Convolutional Neural Networks: Case Studies in Train Stations
arxiv:1901.10553 v1 · 2019-01-22 · cs.CY · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{NP4ODDD3MCLET35YI7ZVXTZZ3U}
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
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4
Citations
5
Replications
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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 | 2026-05-17T23:43:27.957771Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6bf8e18c7b609649efb847f35bcf39dd0e40e592aada4559137ea5983f0b342d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NP4ODDD3MCLET35YI7ZVXTZZ3U \
| 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: 6bf8e18c7b609649efb847f35bcf39dd0e40e592aada4559137ea5983f0b342d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "24ef8bbfe5919ece4de9a440674fc4f9e749901b3f9e6dba1f1bc54620245730",
"cross_cats_sorted": [
"cs.CV"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CY",
"submitted_at": "2019-01-22T14:52:07Z",
"title_canon_sha256": "cf3c8ac2e3940ed862bf4fa6395e05c2e157beff0181ede0748ceb5709a07841"
},
"schema_version": "1.0",
"source": {
"id": "1901.10553",
"kind": "arxiv",
"version": 1
}
}