Pith Number
pith:3V4N6C2M
pith:2022:3V4N6C2MXFNO4UX3VHPPYPXLC4
not attested
not anchored
not stored
refs pending
Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark
arxiv:2206.13996 v1 · 2022-06-28 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{3V4N6C2MXFNO4UX3VHPPYPXLC4}
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 | 2026-07-05T04:35:52.034797Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
dd78df0b4cb95aee52fba9defc3eeb173d0030e8f5d7172907e5a0a296ddaf42
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3V4N6C2MXFNO4UX3VHPPYPXLC4 \
| 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: dd78df0b4cb95aee52fba9defc3eeb173d0030e8f5d7172907e5a0a296ddaf42
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "903ab987ed1e243c958cc721719b40729d05352e5f79c9a627bca9956ea41c0e",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2022-06-28T13:33:06Z",
"title_canon_sha256": "ae4e6bdaaf2b201430d1862e32f57450a7aa5b7c396e1e190891caabae86c33d"
},
"schema_version": "1.0",
"source": {
"id": "2206.13996",
"kind": "arxiv",
"version": 1
}
}