Evidence map›Paper›PMID 39583251›Full record

ArticleData in brief2024

A fish fry dataset for stocking density control and health assessment based on computer vision.

Yuqiang Wu, Huanliang Xu, Bowen Liao, Jia Nie, Chengxi Xu, Ziao Zhang, Zhaoyu Zhai

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Yuqiang WuCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.
Huanliang XuCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.
Bowen LiaoCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.
Jia NieCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.
Chengxi XuCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.
Ziao ZhangCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.
Zhaoyu ZhaiCollege of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fish farming is a promising economic activity that promotes the social development, protects the ecological environment, and enhances the quality of human life. In recent years, various computer vision models have been established for assessing aquaculture density and monitoring fish health. However, existing datasets are generally characterised by larger fish sizes and low density, making them unsuitable for detecting small targets such as fish fry. This paper presents a dataset comprising 1101 images of largemouth bass (

Indexed as

Density controlFry countingHealth assessmentIndustrial aquacultureSmall target detection

Identifiers

PMID39583251
PMCPMC11584590

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.