Pith Number
pith:TP4IOWDE
pith:2024:TP4IOWDECKWLQQAFG2S3BVALMJ
not attested
not anchored
not stored
refs pending
Triple-domain Feature Learning with Frequency-aware Memory Enhancement for Moving Infrared Small Target Detection
arxiv:2406.06949 v2 · 2024-06-11 · cs.CV · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{TP4IOWDECKWLQQAFG2S3BVALMJ}
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
· sign in to
claim
4
Citations
5
Replications
✓
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 | 2026-07-05T09:03:21.179508Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9bf887586412acb8400536a5b0d40b6254d09f5586a67cbbbc6542861350c7ba
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/TP4IOWDECKWLQQAFG2S3BVALMJ \
| 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: 9bf887586412acb8400536a5b0d40b6254d09f5586a67cbbbc6542861350c7ba
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "4238a8b3edc2f1ad95826c99c09b860fe2518431e890029af36adc4f004d05d5",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2024-06-11T05:21:30Z",
"title_canon_sha256": "5a43a2cfe05451e54e1ba77d7a9dc27792d7f8995b741ee97b2c5b39efe872d2"
},
"schema_version": "1.0",
"source": {
"id": "2406.06949",
"kind": "arxiv",
"version": 2
}
}