Evidence map›Paper›PMID 39124084›Full record

ArticleSensors (Basel, Switzerland)2024

Nonintrusive and Effective Volume Reconstruction Model of Swimming Sturgeon Based on RGB-D Sensor.

Kai Lin, Shiyu Zhang, Junjie Hu, Hongsong Li, Wenzhong Guo, Hongxia Hu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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.

  1. Article
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

6 authors.

Kai LinFisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & National Engineering Research Center for Freshwaters (Beijing), Beijing 100068, China.ORCID 0000-0001-9017-9638
Shiyu ZhangSchool of Instrument Science and Opto Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China.ORCID 0000-0002-4806-8982
Junjie HuFisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & National Engineering Research Center for Freshwaters (Beijing), Beijing 100068, China.
Hongsong LiSchool of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
Wenzhong GuoIntelligent Equipment Technology Research Center of Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.
Hongxia HuFisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & National Engineering Research Center for Freshwaters (Beijing), Beijing 100068, China.

Funding

Beijing Academy of Agriculture and Forestry Science Youth Science Foundation QNJJ202401Beijing Natural Science Foundation 6232013Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture, Min-istry of Agriculture and Rural Affairs, P.R. China 2011NYZD2302National Natural Science Foundation of China 32202996
6 · The paper itself

Abstract

The sturgeon is an important commercial aquaculture species in China. The measurement of sturgeon mass plays a remarkable role in aquaculture management. Furthermore, the measurement of sturgeon mass serves as a key phenotype, offering crucial information for enhancing growth traits through genetic improvement. Until now, the measurement of sturgeon mass is usually conducted by manual sampling, which is work intensive and time consuming for farmers and invasive and stressful for the fish. Therefore, a noninvasive volume reconstruction model for estimating the mass of swimming sturgeon based on RGB-D sensor was proposed in this paper. The volume of individual sturgeon was reconstructed by integrating the thickness of the upper surface of the sturgeon, where the difference in depth between the surface and the bottom was used as the thickness measurement. To verify feasibility, three experimental groups were conducted, achieving prediction accuracies of 0.897, 0.861, and 0.883, which indicated that the method can obtain the reliable, accurate mass of the sturgeon. The strategy requires no special hardware or intensive calculation, and it provides a key to uncovering noncontact, high-throughput, and highly sensitive mass evaluation of sturgeon while holding potential for evaluating the mass of other cultured fishes.

Indexed as

AquacultureFishesSwimmingAnimalsdeep learningnonintrusiveRGB-D sensorsturgeonvolume reconstruction

Identifiers

PMID39124084
PMCPMC11314869

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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.