Pith Number
pith:DNWQXEFJ
pith:2023:DNWQXEFJITY7MBFS4R25UUX6FN
not attested
not anchored
not stored
refs pending
Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation
arxiv:2307.07269 v2 · 2023-07-14 · eess.IV · cs.CV · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{DNWQXEFJITY7MBFS4R25UUX6FN}
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 | 2026-07-05T06:33:05.736513Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
1b6d0b90a944f1f604b2e475da52fe2b51f79f7242f4cc1494dafb591354e0ad
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/DNWQXEFJITY7MBFS4R25UUX6FN \
| 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: 1b6d0b90a944f1f604b2e475da52fe2b51f79f7242f4cc1494dafb591354e0ad
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "4730715cc00c2b7db2d9728e3b6e7fe51cfea513da2284638ffbb19eb5b4663f",
"cross_cats_sorted": [
"cs.CV",
"cs.LG"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "eess.IV",
"submitted_at": "2023-07-14T10:50:43Z",
"title_canon_sha256": "ca2e45df97f4a7d2ffe6c45e156b0f1d6a5b9f5103f6121f94ae595982780884"
},
"schema_version": "1.0",
"source": {
"id": "2307.07269",
"kind": "arxiv",
"version": 2
}
}