Cargando…

Study on the Influence of PCA Pre-Treatment on Pig Face Identification with Random Forest

SIMPLE SUMMARY: Pig face recognition plays an important role in the intelligent breeding and accurate management of pigs, and the mobile and embedded applications of this technology in the management of small and medium-sized pig farms are in great demand; therefore, in order to make the model more...

Descripción completa

Detalles Bibliográficos
Autores principales:	Yan, Hongwen, Cai, Songrui, Li, Erhao, Liu, Jianyu, Hu, Zhiwei, Li, Qiangsheng, Wang, Huiting
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10177592/ https://www.ncbi.nlm.nih.gov/pubmed/37174592 http://dx.doi.org/10.3390/ani13091555

Ejemplares similares

Study on the Detection Method for Daylily Based on YOLOv5 under Complex Field Environments
por: Yan, Hongwen, et al.
Publicado: (2023)

PEM-PCA: A Parallel Expectation-Maximization PCA Face Recognition Architecture
por: Rujirakul, Kanokmon, et al.
Publicado: (2014)

Studies on genetic diversity, gene flow and landscape genetic in Avicennia marina: Spatial PCA, Random Forest, and phylogeography approaches
por: Malekmohammadi, Laleh, et al.
Publicado: (2023)

A Fast Segmentation Method for Fire Forest Images Based on Multiscale Transform and PCA
por: Tlig, Lotfi, et al.
Publicado: (2020)

Origin identification of Cornus officinalis based on PCA-SVM combined model
por: Jin, Yueqiang, et al.
Publicado: (2023)

Attention-Guided Instance Segmentation for Group-Raised Pigs
por: Hu, Zhiwei, et al.
Publicado: (2023)

Improving RLRN Image Splicing Detection with the Use of PCA and Kernel PCA
por: Moghaddasi, Zahra, et al.
Publicado: (2014)

PCA-Correlated SNPs for Structure Identification in Worldwide Human Populations
por: Paschou, Peristera, et al.
Publicado: (2007)

Consequences of PCA graphs, SNP codings, and PCA variants for elucidating population structure
por: Gauch, Hugh G., et al.
Publicado: (2019)

Screening Discriminating SNPs for Chinese Indigenous Pig Breeds Identification Using a Random Forests Algorithm
por: Gao, Jun, et al.
Publicado: (2022)

Simultaneous Estimation of Hydrochlorothiazide, Hydralazine Hydrochloride, and Reserpine Using PCA, NAS, and NAS-PCA
por: Sharma, Chetan, et al.
Publicado: (2015)

Duplication of the Posterior Cerebral Artery (PCA) or “True Fetal PCA”: An Extremely Rare Variant
por: Coulier, Bruno
Publicado: (2018)

PCA-based supervised identification of biological soil crusts in multispectral images
por: Fischer, Thomas
Publicado: (2019)

Identification of Plasma Glycosphingolipids as Potential Biomarkers for Prostate Cancer (PCa) Status
por: Snider, Ashley J., et al.
Publicado: (2020)

Molecular identification of wines using in situ liquid SIMS and PCA analysis
por: Cheng, Cuixia, et al.
Publicado: (2023)

Optimization of RiPCA for the Live‐Cell Detection of Pre‐MicroRNA‐Protein Interactions
por: Rosenblum, Sydney L., et al.
Publicado: (2022)

Discussion of the Influence of Multiscale PCA Denoising Methods with Three Different Features
por: Zhang, Chizhou, et al.
Publicado: (2022)

Faces in the forest : the endangered muriqui monkeys of Brazil /
por: Strier, Karen B.
Publicado: (1992)

The PCA total hip system.
Publicado: (1984)

HPTLC-PCA Complementary to HRMS-PCA in the Case Study of Arbutus unedo Antioxidant Phenolic Profiling
por: Maldini, Mariateresa, et al.
Publicado: (2019)

Parameter estimation of the structured illumination pattern based on principal component analysis (PCA): PCA-SIM
por: Chen, Xin, et al.
Publicado: (2023)

Comparing the performance of Kernel PCA Mix Chart with PCA Mix Chart for monitoring mixed quality characteristics
por: Ahsan, Muhammad, et al.
Publicado: (2022)

ISTRF: Identification of sucrose transporter using random forest
por: Chen, Dong, et al.
Publicado: (2022)

Innovative Hybrid Approach for Masked Face Recognition Using Pretrained Mask Detection and Segmentation, Robust PCA, and KNN Classifier
por: Eman, Mohammed, et al.
Publicado: (2023)

Comparing NODAL on N100's and on PCA's
por: Brummer, P J
Publicado: (1989)

Measurable selectors of PCA multifunctions with applications
por: Srebrny, Marian
Publicado: (1984)

Circle of Willis Variants: Fetal PCA
por: Shaban, Amir, et al.
Publicado: (2013)

Flow‐directed PCA for monitoring networks
por: Gallacher, K., et al.
Publicado: (2016)

Improvement of variables interpretability in kernel PCA
por: Briscik, Mitja, et al.
Publicado: (2023)

Elevated YKL40 is associated with advanced prostate cancer (PCa) and positively regulates invasion and migration of PCa cells
por: Jeet, Varinder, et al.
Publicado: (2014)

PCA3 and PCA3-Based Nomograms Improve Diagnostic Accuracy in Patients Undergoing First Prostate Biopsy
por: Ruffion, Alain, et al.
Publicado: (2013)

Assessment of Urban Agglomeration Ecological Sustainability and Identification of Influencing Factors: Based on the 3DEF Model and the Random Forest
por: Li, Zhigang, et al.
Publicado: (2022)

Dynamic Meta-data Network Sparse PCA for Cancer Subtype Biomarker Screening
por: Miao, Rui, et al.
Publicado: (2022)

Fecal source identification using random forest
por: Roguet, Adélaïde, et al.
Publicado: (2018)

Kernel-PCA data integration with enhanced interpretability
por: Reverter, Ferran, et al.
Publicado: (2014)

Detecting inversions with PCA in the presence of population structure
por: Nowling, Ronald J., et al.
Publicado: (2020)

Subject clustering by IF-PCA and several recent methods
por: Chen, Dieyi, et al.
Publicado: (2023)

Clinically significant prostate cancer (csPCa) detection with various prostate sampling schemes based on different csPCa definitions
por: Wang, Fei, et al.
Publicado: (2021)

Application of Principal Component Analysis (PCA) to the Evaluation and Screening of Multiactivity Fungi
por: Yang, Zonglin, et al.
Publicado: (2022)

PCA-Based Incremental Extreme Learning Machine (PCA-IELM) for COVID-19 Patient Diagnosis Using Chest X-Ray Images
por: Kumar, Vinod, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_vcc2lkh697u3sermfofi9fb1i4