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KU Leuven deep cnn classifiers
Deep Cnn Classifiers, supplied by KU Leuven, 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/product/deep+cnn+classifiers/deep+cnn+classifiers/pmc11904658__ao4c09485_si_001-0-0-31
Average 90 stars, based on 1 article reviews
deep cnn classifiers - by Bioz Stars, 2026-09
90/100 stars

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Related Articles

Imaging:

Article Title: DeepMAP: Deep CNN Classifiers Applied to Optical Mapping for Fast and Precise Species-Level Metagenomic Analysis
Article Snippet: .. S1 DeepMAP: Deep CNN classifiers applied to optical mapping for fast and precise species-level metagenomic analysis Sergey Abakumov,† Elizabete Ruppeka-Rupeika,‡ Xiong Chen,‡ Arno Bouwens,¶ Volker Leen,¶ Peter Dedecker,∗,† and Johan Hofkens‡ †KU Leuven, Department of chemistry, Laboratory for Nanobiology, Celestijnenlaan 200G, 3000 Leuven, Belgium ‡KU Leuven, Department of chemistry, Laboratory for Molecular Imaging and Photonics, Celestijnenlaan 200F, 3000 Leuven, Belgium ¶Perseus Biomics, Industriepark 6,3300 Tienen,Belgium E-mail : peter.dedecker@kuleuven.be S2 Supporting information Brief statement in non-sentence format of the contents of the material supplied as Supporting Information: Supplementary Note 1: Image segmentation Supplementary Figure S1: An example of a scanned image and its corresponding segmentation Supplementary Note 2: Simulation framework Supplementary Table S1: Description of reference genomes used in the analysis Supplementary Figure S2: An illustration of potential contribution of the background to the DNA map Supplementary Figure S3: The simulation pipeline for obtaining data for both training the network and validation. ..

Biomarker Discovery:

Article Title: DeepMAP: Deep CNN Classifiers Applied to Optical Mapping for Fast and Precise Species-Level Metagenomic Analysis
Article Snippet: .. S1 DeepMAP: Deep CNN classifiers applied to optical mapping for fast and precise species-level metagenomic analysis Sergey Abakumov,† Elizabete Ruppeka-Rupeika,‡ Xiong Chen,‡ Arno Bouwens,¶ Volker Leen,¶ Peter Dedecker,∗,† and Johan Hofkens‡ †KU Leuven, Department of chemistry, Laboratory for Nanobiology, Celestijnenlaan 200G, 3000 Leuven, Belgium ‡KU Leuven, Department of chemistry, Laboratory for Molecular Imaging and Photonics, Celestijnenlaan 200F, 3000 Leuven, Belgium ¶Perseus Biomics, Industriepark 6,3300 Tienen,Belgium E-mail : peter.dedecker@kuleuven.be S2 Supporting information Brief statement in non-sentence format of the contents of the material supplied as Supporting Information: Supplementary Note 1: Image segmentation Supplementary Figure S1: An example of a scanned image and its corresponding segmentation Supplementary Note 2: Simulation framework Supplementary Table S1: Description of reference genomes used in the analysis Supplementary Figure S2: An illustration of potential contribution of the background to the DNA map Supplementary Figure S3: The simulation pipeline for obtaining data for both training the network and validation. ..



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