Evidence map›Paper›PMID 40096311›Full record

ArticleSensors (Basel, Switzerland)2025

Enhancing Underwater Images of a Bionic Horseshoe Crab Robot Using an Artificial Lateral Inhibition Network.

Yuke Ma, Liang Zheng, Yan Piao, Yu Wang, Hui Yu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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.

Yuke MaSchool of Electronic and Information Engineering, Changchun University of Science and Technology, 7089 Weixing Road, Changchun 130022, China.ORCID 0009-0000-3086-3868
Liang ZhengSchool of the Electrical and Information Engineering, Jilin Agricultural Science and Technology University, 77 Hanlin Road, Jilin 132101, China.
Yan PiaoSchool of Electronic and Information Engineering, Changchun University of Science and Technology, 7089 Weixing Road, Changchun 130022, China.
Yu WangSchool of Electronic and Information Engineering, Changchun University of Science and Technology, 7089 Weixing Road, Changchun 130022, China.
Hui YuSchool of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin 132022, China.

Funding

Digital Agriculture key discipline of Jilin Province Foundation JLXK20180319Doctoral startup fund project Jilin Agricultural Science and Technology University No. [2021] 7004Science and Technology Development Plan Project of Jilin Province YDZJ202201ZYTS692Smart Agricultural Engineering Research Centre of Jilin Province Foundation JLNKU2015
6 · The paper itself

Abstract

This paper proposes an underwater image enhancement technology based on an artificial lateral inhibition network (ALIN) generated in the compound eye of a bionic horseshoe crab robot (BHCR). The concept of a horizontal suppression network is applied to underwater image processing with the aim of achieving low energy consumption, high efficiency processing, and adaptability to limited computing resources. The lateral inhibition network has the effect of "enhancing the center and suppressing the surroundings". In this paper, a pattern recognition algorithm is used to compare and analyze the images obtained by an artificial lateral inhibition network and eight main underwater enhancement algorithms (white balance, histogram equalization, multi-scale Retinex, and dark channel). Therefore, we can evaluate the application of the artificial lateral inhibition network in underwater image enhancement and the deficiency of the algorithm. The experimental results show that the ALIN plays an obvious role in enhancing the important information in underwater image processing technology. Compared with other algorithms, this algorithm can effectively improve the contrast between the highlight area and the shadow area in underwater image processing, solve the problem that the information of the characteristic points of the collected image is not prominent, and achieve the unique effect of suppressing the intensity of other pixel points without information. Finally, we conduct target recognition verification experiments to assess the ALIN's performance in identifying targets underwater with the BHCR in static water environments. The experiments confirm that the BHCR can maneuver underwater using multiple degrees of freedom (MDOF) and successfully acquire underwater targets.

Indexed as

amphibious bionic robotbionic horseshoe crab robot (BHCR)lateral inhibitionmultiple underwater movement

Identifiers

PMID40096311
PMCPMC11902550

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Registered trials

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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.