Pith Number

pith:BXZ7AUJM

pith:2026:BXZ7AUJM63KASL3TZ2IO4LUN7J

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CANSURF: An ASV-View Can Dataset and Benchmark for Detection and Tracking of Surface-Level Debris

Abdullah Moosa, Mostafa Elemam, Zahra F. Rahmatullah, Zaid Aljundi

A dataset tailored to aluminum cans on water surfaces improves object detection accuracy twelve times over generic training sets.

arxiv:2605.16774 v1 · 2026-05-16 · cs.CV · cs.AI

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4 Citations 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

Training YOLOv11 on CANSURF boosts performance 12x over generic datasets, highlighting the dataset's value.

C2weakest assumption

The collected raw images and the ten augmentation types produce a training distribution that is sufficiently representative of real ASV operating conditions including glare, ripples, and partial submersion.

C3one line summary

Presents the CANSURF dataset for surface-level aluminum can detection from ASV viewpoints and shows that training YOLOv11 on it yields a 12x performance boost over generic datasets along with stable tracking results.

References

17 extracted · 17 resolved · 2 Pith anchors

[1] Marine debris handling guide- lines, 2020

[2] 2020 international coastal cleanup: By the numbers, 2020

[3] Marida: A benchmark for marine debris detection from sentinel-2 remote sensing data, 2022

[4] Trash-icra19: A bounding box labeled dataset of underwater trash, 2020

[5] Trashcan 1.0: An instance- segmentation labeled dataset of trash observations, 2020

Receipt and verification

First computed	2026-05-20T00:03:21.281079Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

0df3f0512cf6d4092f73ce90ee2e8dfa5bf261f67132f7ebed4aaacf76a157cf

Aliases

arxiv: 2605.16774 · arxiv_version: 2605.16774v1 · doi: 10.48550/arxiv.2605.16774 · pith_short_12: BXZ7AUJM63KA · pith_short_16: BXZ7AUJM63KASL3T · pith_short_8: BXZ7AUJM

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/BXZ7AUJM63KASL3TZ2IO4LUN7J \
  | 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: 0df3f0512cf6d4092f73ce90ee2e8dfa5bf261f67132f7ebed4aaacf76a157cf

Canonical record JSON

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      "cs.AI"
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-16T02:53:57Z",
    "title_canon_sha256": "e2ce5c2e3e01841d45f61a4c05e8a0214e483239f1bc4777a8c28184f9583d54"
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    "kind": "arxiv",
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