ArticleAnimals : an open access journal from MDPI2023
Study on the Influence of PCA Pre-Treatment on Pig Face Identification with Random Forest.
Article in Animals : an open access journal from MDPI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed.
- Weakly supervised learning through box annotations for pig instance segmentation.Scientific reports · 2025Article
- Study on the Impact of LDA Preprocessing on Pig Face Identification with SVM.Animals : an open access journal from MDPI · 2025Article
- Attention-Guided Instance Segmentation for Group-Raised Pigs.Animals : an open access journal from MDPI · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
To explore the application of a traditional machine learning model in the intelligent management of pigs, in this paper, the influence of PCA pre-treatment on pig face identification with RF is studied. By this testing method, the parameters of two testing schemes, one adopting RF alone and the other adopting RF + PCA, were determined to be 65 and 70, respectively. With individual identification tests carried out on 10 pigs, accuracy, recall, and f1-score were increased by 2.66, 2.76, and 2.81 percentage points, respectively. Except for the slight increase in training time, the test time was reduced to 75% of the old scheme, and the efficiency of the optimized scheme was greatly improved. It indicates that PCA pre-treatment positively improved the efficiency of individual pig identification with RF. Furthermore, it provides experimental support for the mobile terminals and the embedded application of RF classifiers.
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Registered trials
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