Evidence map›Paper›PMID 41095059›Full record

ArticleSensors (Basel, Switzerland)2025

Research on Instance Segmentation Algorithm for Caged Chickens in Infrared Images Based on Improved Mask R-CNN.

Youqing Chen, Hang Liu, Lun Wang, Chen Chen, Siyu Li, Binyuan Zhong, Jihui Qiao, Rong Ye, Tong Li

Abstract read
PubMed Full text at PMC Publisher
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

9 authors.

Youqing ChenCollege of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming 650201, China.
Hang LiuThe Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province, Yunnan Agricultural University, Kunming 650201, China.
Lun WangCollege of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming 650201, China.
Chen ChenSchool of Big Data, Yunnan Agricultural University, Kunming 650201, China.
Siyu LiThe Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province, Yunnan Agricultural University, Kunming 650201, China.
Binyuan ZhongThe Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province, Yunnan Agricultural University, Kunming 650201, China.
Jihui QiaoCollege of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming 650201, China.
Rong YeThe Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province, Yunnan Agricultural University, Kunming 650201, China.
Tong LiThe Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province, Yunnan Agricultural University, Kunming 650201, China.ORCID 0000-0002-3257-213X

Funding

Tong Li 202302AE090020Tong Li 202305AF150126Tong Li 202407AB110010
6 · The paper itself

Abstract

Infrared images of caged chickens can provide valuable insights into their health status. Accurately detecting and segmenting individual chickens in these images is essential for effective health monitoring in large-scale chicken farming. However, the presence of obstacles such as cages, feeders, and drinkers can obscure the chickens, while clustering and overlapping among them may further hinder segmentation accuracy. This study proposes a Mask R-CNN-based instance segmentation algorithm specifically designed for caged chickens in infrared images. The backbone network is enhanced by incorporating the CBAM within this algorithm, which is further combined with the AC-FPN architecture to improve the model's ability to extract features. Experimental results demonstrate that the model achieves average AP and AR

Indexed as

ChickensImage Processing, Computer-AssistedNeural Networks, ComputerAlgorithmsAnimalsInfrared RaysAC-FPNcaged chickensCBAMinstance segmentationMask R-CNN

Identifiers

PMID41095059
PMCPMC12526962

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.