Pith Number
pith:AZHIHII4
pith:2016:AZHIHII42ZZN4G5HSJBINVS7NM
not attested
not anchored
not stored
refs pending
Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks
arxiv:1608.00203 v1 · 2016-07-31 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{AZHIHII42ZZN4G5HSJBINVS7NM}
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
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claim
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 | 2026-05-18T01:10:12.237415Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
064e83a11cd672de1ba7924286d65f6b127ff3e7b907ca464d9cc59ed91b3919
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/AZHIHII42ZZN4G5HSJBINVS7NM \
| 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: 064e83a11cd672de1ba7924286d65f6b127ff3e7b907ca464d9cc59ed91b3919
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "4bf51a8dc97ea89699e892dd77b9c0f548f348b7ea316cb68347e01ce61fe09e",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2016-07-31T09:28:28Z",
"title_canon_sha256": "70b36b6b0a5c5a1cb338c70204d16b4087ed69c1bdb9f4b79f533f028a38cd78"
},
"schema_version": "1.0",
"source": {
"id": "1608.00203",
"kind": "arxiv",
"version": 1
}
}