Pith Number
pith:EPSNASJP
pith:2020:EPSNASJPEUO4PPF7LQMDTXMLGL
not attested
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refs pending
A Feasibility study for Deep learning based automated brain tumor segmentation using Magnetic Resonance Images
arxiv:2012.11952 v1 · 2020-12-22 · eess.IV · cs.CV · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{EPSNASJPEUO4PPF7LQMDTXMLGL}
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 | 2026-07-05T02:01:23.286583Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
23e4d0492f251dc7bcbf5c1839dd8b32f3ca49e62921a9be91b69e21970177be
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/EPSNASJPEUO4PPF7LQMDTXMLGL \
| 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: 23e4d0492f251dc7bcbf5c1839dd8b32f3ca49e62921a9be91b69e21970177be
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "8e91cf4f56ef0f50aebbde4f806b6446f08a9a4bfaeea28c49505aa7462508ff",
"cross_cats_sorted": [
"cs.CV",
"cs.LG"
],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "eess.IV",
"submitted_at": "2020-12-22T12:11:42Z",
"title_canon_sha256": "20639a20afb2e3c9986ccb2a367b44e9108886fd6668ea072fcda9259c6c94ba"
},
"schema_version": "1.0",
"source": {
"id": "2012.11952",
"kind": "arxiv",
"version": 1
}
}