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Image Search Results
Journal: PLoS ONE
Article Title: High Resolution Niche Models of Malaria Vectors in Northern Tanzania: A New Capacity to Predict Malaria Risk?
doi: 10.1371/journal.pone.0009396
Figure Lengend Snippet: Comparison of malaria vector species' niche models using unsupervised vs. supervised land cover classifications.
Article Snippet: Ascii grid layers for unsupervised and
Techniques: Comparison, Plasmid Preparation
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: Various parameters for hyper-tuning of the proposed SCovNet.
Article Snippet: Confusion matrices of
Techniques: Shear
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: Confusion matrices of SCovNet Classification: (a) 18-layered; (b) 50-layered; (c) 101-layered for the Kaggle database, respectively.
Article Snippet: Confusion matrices of
Techniques:
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: Performance parameters (Kaggle database).
Article Snippet: Confusion matrices of
Techniques:
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: Confusion matrices of SCovNet Classification: (a) 18-layered; (b) 50-layered; (c) 101-layered for GitHub database respectively.
Article Snippet: Confusion matrices of
Techniques:
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: Performance parameters (GitHub database).
Article Snippet: Confusion matrices of
Techniques:
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: A curves of: (a) Receiver operating characteristic (ROC) for the proposed SCovNet model; (b) Precision-Recall curve of the proposed SCovNet deep learning model.
Article Snippet: Confusion matrices of
Techniques:
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: Ablation Study of the proposed SCovNet on Git-Hub database
Article Snippet: Confusion matrices of
Techniques:
Journal: Biocybernetics and Biomedical Engineering
Article Title: SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
doi: 10.1016/j.bbe.2023.01.005
Figure Lengend Snippet: Performance of the proposed work with other similar studies.
Article Snippet: Confusion matrices of
Techniques: