Review



lbp descriptor  (Thermo Fisher)


Bioz Verified Symbol Thermo Fisher is a verified supplier
Bioz Manufacturer Symbol Thermo Fisher manufactures this product  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    Thermo Fisher lbp descriptor
    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures
    Lbp Descriptor, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/lbp descriptor/product/Thermo Fisher
    Average 90 stars, based on 1 article reviews
    lbp descriptor - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis"

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    Journal: Soft Computing

    doi: 10.1007/s00500-022-06886-3

    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures
    Figure Legend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures

    Techniques Used:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Cpu Time measures
    Figure Legend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Cpu Time measures

    Techniques Used:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Accuracy measures
    Figure Legend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Accuracy measures

    Techniques Used:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Selection ratio measures
    Figure Legend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Selection ratio measures

    Techniques Used: Selection

    The impact of features descriptors on the performance of AOA against other recent optimizers over Recall measures
    Figure Legend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Recall measures

    Techniques Used:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Precision measures
    Figure Legend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Precision measures

    Techniques Used:

    The impact of features descriptors on the performance of AOA against other recent optimizers over F-score measures
    Figure Legend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over F-score measures

    Techniques Used:

    Comparative performance in terms of accuracy with the existing methods– GT dataset
    Figure Legend Snippet: Comparative performance in terms of accuracy with the existing methods– GT dataset

    Techniques Used:

    Statistical study using Wilcoxon’s test ( In bold best values \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p <0.05$$\end{document} p < 0.05 , which implies that AOA is substantial against algorithm X)
    Figure Legend Snippet: Statistical study using Wilcoxon’s test ( In bold best values \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p <0.05$$\end{document} p < 0.05 , which implies that AOA is substantial against algorithm X)

    Techniques Used:

    Comparative performance in terms of accuracy with the existing approaches–FEI dataset
    Figure Legend Snippet: Comparative performance in terms of accuracy with the existing approaches–FEI dataset

    Techniques Used:

    Comparative performance in terms of accuracy with the existing approaches–Gallagher’s dataset under Dago’s protocol
    Figure Legend Snippet: Comparative performance in terms of accuracy with the existing approaches–Gallagher’s dataset under Dago’s protocol

    Techniques Used:



    Similar Products

    lbp texture descriptors  (Optics and Photonics)
    90
    Optics and Photonics lbp texture descriptors
    Lbp Texture Descriptors, supplied by Optics and Photonics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/lbp texture descriptors/product/Optics and Photonics
    Average 90 stars, based on 1 article reviews
    lbp texture descriptors - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    lbp descriptor  (Thermo Fisher)
    90
    Thermo Fisher lbp descriptor
    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures
    Lbp Descriptor, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/lbp descriptor/product/Thermo Fisher
    Average 90 stars, based on 1 article reviews
    lbp descriptor - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    lbp descriptor  (MathWorks Inc)
    90
    MathWorks Inc lbp descriptor
    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures
    Lbp Descriptor, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/lbp descriptor/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    lbp descriptor - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    lbp descriptor block  (Xilinx Inc)
    90
    Xilinx Inc lbp descriptor block
    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures
    Lbp Descriptor Block, supplied by Xilinx Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/lbp descriptor block/product/Xilinx Inc
    Average 90 stars, based on 1 article reviews
    lbp descriptor block - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    lbp texture descriptor  (Informa UK Limited)
    90
    Informa UK Limited lbp texture descriptor
    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures
    Lbp Texture Descriptor, supplied by Informa UK Limited, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/lbp texture descriptor/product/Informa UK Limited
    Average 90 stars, based on 1 article reviews
    lbp texture descriptor - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier
    lbp texture descriptor  (Wolters Kluwer Health)
    90
    Wolters Kluwer Health lbp texture descriptor
    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures
    Lbp Texture Descriptor, supplied by Wolters Kluwer Health, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/lbp texture descriptor/product/Wolters Kluwer Health
    Average 90 stars, based on 1 article reviews
    lbp texture descriptor - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over fitness measures

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Cpu Time measures

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Cpu Time measures

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Accuracy measures

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Accuracy measures

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Selection ratio measures

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Selection ratio measures

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques: Selection

    The impact of features descriptors on the performance of AOA against other recent optimizers over Recall measures

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Recall measures

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    The impact of features descriptors on the performance of AOA against other recent optimizers over Precision measures

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over Precision measures

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    The impact of features descriptors on the performance of AOA against other recent optimizers over F-score measures

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: The impact of features descriptors on the performance of AOA against other recent optimizers over F-score measures

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    Comparative performance in terms of accuracy with the existing methods– GT dataset

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: Comparative performance in terms of accuracy with the existing methods– GT dataset

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    Statistical study using Wilcoxon’s test ( In bold best values \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p <0.05$$\end{document} p < 0.05 , which implies that AOA is substantial against algorithm X)

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: Statistical study using Wilcoxon’s test ( In bold best values \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p <0.05$$\end{document} p < 0.05 , which implies that AOA is substantial against algorithm X)

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    Comparative performance in terms of accuracy with the existing approaches–FEI dataset

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: Comparative performance in terms of accuracy with the existing approaches–FEI dataset

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques:

    Comparative performance in terms of accuracy with the existing approaches–Gallagher’s dataset under Dago’s protocol

    Journal: Soft Computing

    Article Title: An Intelligent handcrafted feature selection using Archimedes optimization algorithm for facial analysis

    doi: 10.1007/s00500-022-06886-3

    Figure Lengend Snippet: Comparative performance in terms of accuracy with the existing approaches–Gallagher’s dataset under Dago’s protocol

    Article Snippet: For this, we have integrated three textural descriptors, including HOG, LBP, and GLCM tested over smallest datasets (GT and FEI) and largest dataset (Gallagher’s database).

    Techniques: