resnet18 (Kaggle Inc)
86
Structured Review
Kaggle Inc
resnet18
Resnet18, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/resnet18/resnet18/pmc12431290-290-3-7
Average 86 stars, based on 1 article reviews
Resnet18, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/resnet18/resnet18/pmc12431290-290-3-7
Average 86 stars, based on 1 article reviews
resnet18 - by Bioz Stars,
2026-10
86/100 stars
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Related Articles
Transformation Assay:Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System. Article Snippet: Table 11 summarizes the F1-score for ResNet18, ResNet34, VGG11, and AlexNet regarding the threshold ranges in the Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System. Article Snippet: The F1-score of Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System Article Snippet: The F1-score of Article Title: Maize disease classification using transfer learning and convolutional neural network with weighted loss Article Snippet: Proposed Research with first dataset , ResNet18, VGG16, EfficientNet-b0 , 95.838 % ( Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System. Article Snippet: On the Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System Article Snippet: We performed deep learning analysis on the test data with categorized threshold ranges for CPBD and PIQE. summarizes the F1-score for ResNet18, ResNet34, VGG11, and AlexNet regarding the threshold ranges in the Comparison:Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System. Article Snippet: Table 11 summarizes the F1-score for ResNet18, ResNet34, VGG11, and AlexNet regarding the threshold ranges in the Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System. Article Snippet: The F1-score of Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System Article Snippet: The F1-score of Article Title: Maize disease classification using transfer learning and convolutional neural network with weighted loss Article Snippet: Proposed Research with first dataset , ResNet18, VGG16, EfficientNet-b0 , 95.838 % ( Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System. Article Snippet: On the Article Title: Optimizing Deep Learning-Based Crack Detection Using No-Reference Image Quality Assessment in a Mobile Tunnel Scanning System Article Snippet: We performed deep learning analysis on the test data with categorized threshold ranges for CPBD and PIQE. summarizes the F1-score for ResNet18, ResNet34, VGG11, and AlexNet regarding the threshold ranges in the |
