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pith:HAJRRVRD

pith:2026:HAJRRVRDFZHVH4QIOO73KF6S5S

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Benchmarking Deep Learning and Statistical Target Detection Methods for PFM-1 Landmine Detection in UAV Hyperspectral Imagery

Emmett J. Ientilucci, Prasanna Reddy Pulakurthi, Ramesh Bhatta, Sagar Lekhak

A lightweight spectral neural network achieves the highest average precision for detecting sparse PFM-1 landmine pixels in UAV hyperspectral imagery, outperforming classical detectors under precision-focused metrics.

arxiv:2602.10434 v3 · 2026-02-11 · eess.IV

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Claims

C1strongest claim

While all methods achieve high ROC-AUC on an independent test set, the ACE method observes the highest AUC of 0.989. However, because target pixels are extremely sparse relative to background, ROC-AUC alone can be misleading; under precision-focused evaluation (PR and AP), the Spectral-NN outperforms classical detectors, achieving the highest AP.

C2weakest assumption

That performance measured on inert PFM-1 targets in the released VNIR dataset will generalize to live mines, different soils, lighting conditions, or other landmine types without retraining or additional calibration.

C3one line summary

A proposed lightweight Spectral Neural Network with Parametric Mish activations achieves the highest average precision for sparse PFM-1 landmine detection in UAV hyperspectral imagery, outperforming ACE, SAM, MF, and CEM on precision-recall metrics despite lower ROC-AUC.

Receipt and verification

First computed	2026-06-02T01:03:42.791619Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

381318d6232e4f53f20873bfb517d2ecb1fb818dda691badcde5e071c03265f0

Aliases

arxiv: 2602.10434 · arxiv_version: 2602.10434v3 · doi: 10.48550/arxiv.2602.10434 · pith_short_12: HAJRRVRDFZHV · pith_short_16: HAJRRVRDFZHVH4QI · pith_short_8: HAJRRVRD

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/HAJRRVRDFZHVH4QIOO73KF6S5S \
  | 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: 381318d6232e4f53f20873bfb517d2ecb1fb818dda691badcde5e071c03265f0

Canonical record JSON

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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "eess.IV",
    "submitted_at": "2026-02-11T02:25:32Z",
    "title_canon_sha256": "3c25053939d605b38a769b07dca7a0ee8f8416653a286f282e3bcf5ace9ab35c"
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