Pith Number
pith:G5HDYVES
pith:2017:G5HDYVESVWSS6MVYLHFIQU6QP3
not attested
not anchored
not stored
refs pending
Unsupervised Multi Class Segmentation of 3D Images with Intensity Inhomogeneities
arxiv:1702.02300 v2 · 2017-02-08 · math.NA
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{G5HDYVESVWSS6MVYLHFIQU6QP3}
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 | 2026-05-18T00:44:57.358519Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
374e3c5492ada52f32b859ca8853d07ecb4c65c1d1fd076e94216f810e5b75c4
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/G5HDYVESVWSS6MVYLHFIQU6QP3 \
| 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: 374e3c5492ada52f32b859ca8853d07ecb4c65c1d1fd076e94216f810e5b75c4
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "886efb0727c3024ecdc600bd6e275acbb5637c340d670df0145487727c229535",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "math.NA",
"submitted_at": "2017-02-08T06:37:40Z",
"title_canon_sha256": "6bb38f23244e945e1ab2947c510c2a3b16f6963fb5b51652adfc9d88b0f1b027"
},
"schema_version": "1.0",
"source": {
"id": "1702.02300",
"kind": "arxiv",
"version": 2
}
}