Pith Number

pith:C5XYIFPT

pith:2026:C5XYIFPTEAGBM3FPCFOENGZ5N4

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PipeMFL-240K: A Large-scale Dataset and Benchmark for Object Detection in Pipeline Magnetic Flux Leakage Imaging

Guanlin Liu, Haolin Wang, Honghe Chen, Huadong Song, Songxiao Yang, Tianyi Qu, Wenguang Hu, Xiaoting Guo, Yafei Ou

PipeMFL-240K provides the first large-scale public dataset and benchmark for detecting defects in pipeline magnetic flux leakage images.

arxiv:2602.07044 v3 · 2026-02-04 · cs.CV · cs.AI

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\pithnumber{C5XYIFPTEAGBM3FPCFOENGZ5N4}

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Record completeness

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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

As the first public dataset and the first benchmark of this scale and scope for pipeline MFL inspection, it provides a critical foundation for efficient pipeline diagnostics as well as maintenance planning and is expected to accelerate algorithmic innovation and reproducible research in MFL-based pipeline integrity assessment.

C2weakest assumption

The collected images and annotations from the 12 pipelines are representative of real-world MFL inspection complexity and that the bounding-box labels are consistently high-quality across the entire dataset.

C3one line summary

PipeMFL-240K is the first large public dataset and benchmark for object detection in pipeline MFL imaging, with 249k images across 12 long-tailed categories featuring tiny objects and high intra-class variability.

Receipt and verification

First computed	2026-05-25T02:01:14.558399Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

176f8415f3200c166caf115c469b3d6f3b69fef6f5c7b14ae275647f45ccfee3

Aliases

arxiv: 2602.07044 · arxiv_version: 2602.07044v3 · doi: 10.48550/arxiv.2602.07044 · pith_short_12: C5XYIFPTEAGB · pith_short_16: C5XYIFPTEAGBM3FP · pith_short_8: C5XYIFPT

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/C5XYIFPTEAGBM3FPCFOENGZ5N4 \
  | 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: 176f8415f3200c166caf115c469b3d6f3b69fef6f5c7b14ae275647f45ccfee3

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e04f60a64ce966b559ab2f34652ffc3774a56026349f46842c92191b7aab5f9c",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-02-04T04:43:32Z",
    "title_canon_sha256": "07a8abf8a845497b27fc08d9e25b0d54403cf899e7e4e85a4b6b87e571e1e08f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2602.07044",
    "kind": "arxiv",
    "version": 3
  }
}