Pith Number
pith:2NIQZGPB
pith:2017:2NIQZGPBZGJEEMV5USTKIMMBXU
not attested
not anchored
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refs pending
Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes
arxiv:1711.00049 v2 · 2017-10-31 · cs.CV · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{2NIQZGPBZGJEEMV5USTKIMMBXU}
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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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 | 2026-05-18T00:13:05.119560Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d3510c99e1c9924232bda4a6a43181bd354f0e712a6482343f776b3dea515394
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2NIQZGPBZGJEEMV5USTKIMMBXU \
| 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: d3510c99e1c9924232bda4a6a43181bd354f0e712a6482343f776b3dea515394
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "1331b84fea1b2fcc7a98d8ac6e20a239f5d2b8d2d45ea019982a7060f15d2b0b",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2017-10-31T18:37:28Z",
"title_canon_sha256": "cfdc2b3b31c7a9a10d0b15ce8f1d55a9a7501e9d89d1ca0ac4ef14f557018014"
},
"schema_version": "1.0",
"source": {
"id": "1711.00049",
"kind": "arxiv",
"version": 2
}
}