Pith Number

pith:ERNANDKA

pith:2026:ERNANDKA7K6PLLWE2WYI2KU3WK

not attested not anchored not stored refs resolved

Vision-Based Water Level and Flow Estimation

ZhiXin Sun

An integrated vision framework using physical priors and filtering improves accuracy of water level and flow estimates.

arxiv:2605.14645 v1 · 2026-05-14 · cs.CV · cs.AI

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{ERNANDKA7K6PLLWE2WYI2KU3WK}

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.

Claims

C1strongest claim

By leveraging physical priors and robust filtering strategies, we improve the accuracy of water level detection and flow estimation.

C2weakest assumption

That integrating SOTA vision models with statistical modeling and physical priors will effectively overcome environmental sensitivity, limited precision, and calibration challenges in real-world conditions.

C3one line summary

An integrated framework is proposed that combines SOTA vision models with statistical modeling and physical priors to improve accuracy in water level detection and flow estimation.

References

22 extracted · 22 resolved · 1 Pith anchors

[1] Application of deep learning techniques in water level measurement: Combining improved segformer- unet model with virtual water gauge.Applied Sciences, 13(9), 2023 2023 · doi:10.3390/app13095614

[2] Reviving iterative training with mask guidance for interactive segmentation.arXiv preprint arXiv:2102.06583, 2021 2021

[3] SAM 2: Segment Anything in Images and Videos 2024 · arXiv:2408.00714

[4] Implementation of inverse perspective mapping for camera- vision water-level measurements 2020 · doi:10.1109/ics51289.2020.00075

[5] S. M. H. Erfani, C. Smith, Z. Wu, E. A. Shamsabadi, F. Khatami, A. R. J. Downey, J. Imran, and E. Goharian. Eye of horus: a vision-based framework for real-time water level measurement.Hy- drology and 2023 · doi:10.5194/hess-27-4135-2023

Receipt and verification

First computed	2026-05-17T23:39:03.852182Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

245a068d40fabcf5aec4d5b08d2a9bb2b763f5c50370afbd540857c35c8d6154

Aliases

arxiv: 2605.14645 · arxiv_version: 2605.14645v1 · doi: 10.48550/arxiv.2605.14645 · pith_short_12: ERNANDKA7K6P · pith_short_16: ERNANDKA7K6PLLWE · pith_short_8: ERNANDKA

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/ERNANDKA7K6PLLWE2WYI2KU3WK \
  | 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: 245a068d40fabcf5aec4d5b08d2a9bb2b763f5c50370afbd540857c35c8d6154

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4ea2beaf15207e220102d9bd66879ad76dea0c2e4abaa875593593fb19d668e1",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-14T10:01:59Z",
    "title_canon_sha256": "9432d6a590ae576959c3d955625966c58d764367f49b85f609e14da75c7b1b0d"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14645",
    "kind": "arxiv",
    "version": 1
  }
}