pith. sign in
Pith Number

pith:B27HG2WX

pith:2017:B27HG2WXK2F5YJVKF4ZM7EURUA
not attested not anchored not stored refs pending

Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures

Amir Hossein Harati Nejad Torbati, Iyad Obeid, Joseph Picone, Meysam Golmohammadi, Silvia Lopez de Diego

arxiv:1712.09771 v1 · 2017-12-28 · cs.LG · eess.SP · q-bio.NC · stat.ML

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{B27HG2WXK2F5YJVKF4ZM7EURUA}

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 open · sign in to claim
4 Citations open
5 Replications open
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 2026-05-18T00:27:05.601218Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

0ebe736ad7568bdc26aa2f32cf9291a02f443f44f5270a929476eabc1889c21e

Aliases

arxiv: 1712.09771 · arxiv_version: 1712.09771v1 · doi: 10.48550/arxiv.1712.09771 · pith_short_12: B27HG2WXK2F5 · pith_short_16: B27HG2WXK2F5YJVK · pith_short_8: B27HG2WX
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/B27HG2WXK2F5YJVKF4ZM7EURUA \
  | 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: 0ebe736ad7568bdc26aa2f32cf9291a02f443f44f5270a929476eabc1889c21e
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "4785a6adaf8066a2a36e60efee1325bbc8a8d112792f63072c907988f4db4a0c",
    "cross_cats_sorted": [
      "eess.SP",
      "q-bio.NC",
      "stat.ML"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2017-12-28T06:22:28Z",
    "title_canon_sha256": "01b4f74609fac6ee7557d9c8102d91406b7b68bd066e0ff2edcb2ada57e4c433"
  },
  "schema_version": "1.0",
  "source": {
    "id": "1712.09771",
    "kind": "arxiv",
    "version": 1
  }
}