Pith Number

pith:5SZSZSTC

pith:2026:5SZSZSTCYK5IIOEFPXTTX24ILB

not attested not anchored not stored refs resolved

On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning

Dongwei Zhao, Kexin Zhang, Lixin Li, Rui Li, Wensheng Lin, Xin Zhang, Yuna Yan, Zhu Han

A Swin Transformer semantic communication system with federated learning improves UAV image transmission quality by at least 5.7 dB PSNR while keeping raw data private.

arxiv:2605.12566 v1 · 2026-05-12 · eess.IV · cs.LG

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\usepackage{pith}
\pithnumber{5SZSZSTCYK5IIOEFPXTTX24ILB}

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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.

Claims

C1strongest claim

Simulation experiments conducted on the CIFAR-10 dataset demonstrate that the proposed STSC framework achieves at least 5.7 dB improvement in Peak Signal-to-Noise Ratio (PSNR) compared to DeepJSCC baselines, while also showing superior convergence and generalization performance.

C2weakest assumption

That performance gains measured on the CIFAR-10 dataset under simulated conditions will hold for real UAV deployments facing actual bandwidth limits, channel noise, and privacy regulations.

C3one line summary

A Swin Transformer-based semantic communication framework with federated learning reports 5.7 dB PSNR gains over DeepJSCC baselines for UAV image transmission on CIFAR-10.

References

41 extracted · 41 resolved · 2 Pith anchors

[1] Rethink- ing modern communication from semantic coding to semantic communication 2023

[2] Beyond transmitting bits: Context, semantics, and task-oriented communications 2023

[3] FSSC: Federated learning of transformer neural networks for semantic image communication 2024

[4] FLSC-CI: Federated learning and semantic communication empowered multimodal terminal col- laborative inferencing framework for IoT businesses 2026

[5] Federated learning based audio semantic communication over wireless net- works 2021

Receipt and verification

First computed	2026-05-18T03:10:01.864802Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

ecb32cca62c2ba8438857de73beb885869e425fcbe1e3e0eeb550001a9b06fd6

Aliases

arxiv: 2605.12566 · arxiv_version: 2605.12566v1 · doi: 10.48550/arxiv.2605.12566 · pith_short_12: 5SZSZSTCYK5I · pith_short_16: 5SZSZSTCYK5IIOEF · pith_short_8: 5SZSZSTC

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/5SZSZSTCYK5IIOEFPXTTX24ILB \
  | 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: ecb32cca62c2ba8438857de73beb885869e425fcbe1e3e0eeb550001a9b06fd6

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "102b19d1d016df703a0005bcbcf35d10d93b82140aae9988fab3851b81e1f17d",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "eess.IV",
    "submitted_at": "2026-05-12T09:18:53Z",
    "title_canon_sha256": "ef8654af8b946e296f534ca67bff845b30d181565cdd9ab15511184ae776aa27"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12566",
    "kind": "arxiv",
    "version": 1
  }
}