Bounded Graph Conditioning for LiDAR 3D Object Detection Under Sensor Degradation.

Xiuping Li, Xiyan Sun, Jingjing Li, Yuanfa Ji, Wentao Fu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Physics-Guided Multi-GSO Spectral Filtering for Degradation-Aware Automotive Radar Point-Cloud Detection.Sensors (Basel, Switzerland) · 2026
Article

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xiuping LiSchool of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.ORCID 0009-0001-4771-9587

Xiyan SunSchool of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.ORCID 0000-0002-4227-2499

Jingjing LiSchool of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.ORCID 0000-0002-1908-4481

Yuanfa JiSchool of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.ORCID 0000-0001-8092-6679

Wentao FuSchool of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.ORCID 0000-0002-8796-2565

Funding

Guangxi Science and Technology Department AA24206043Guangxi Science and Technology Department AA24263006Guangxi Science and Technology Department AA24263010Guangxi Science and Technology Department AD25069103Nanning Scientific Research and Technology Development Program 20231011Nanning Scientific Research and Technology Development Program 20231029National Natural Science Foundation of China 62471153National Natural Science Foundation of China U23A20280National Natural Science Foundation of China U25A20397

6 · The paper itself

Abstract

Light Detection and Ranging (LiDAR) three-dimensional (3D) object detection degrades under point sparsity, outliers, coordinate noise, and calibration drift, yet detector evaluation remains largely limited to clean benchmarks. This study focuses on sensing robustness rather than detector redesign. We introduce Bounded Graph Conditioning (BGC)-a deterministic pre-voxelization front-end that applies

Indexed as

3D object detectionautonomous drivinggraph conditioningLiDAR sensingoperating boundarysensor degradation

Identifiers

PMID42122395

DOI10.3390/s26092667

PMCPMC13165598

What OpenQuestion holds

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.