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efficientnet multiclass  (EyePACS LLC)
90
EyePACS LLC efficientnet multiclass
Accuracy of each architecture for each dataset for <t>multiclass</t> problem (> 90% dark, > 80% medium otherwise light).
Efficientnet Multiclass, supplied by EyePACS LLC, 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/efficientnet multiclass/product/EyePACS LLC
Average 90 stars, based on 1 article reviews
efficientnet multiclass - by Bioz Stars, 2026-04
90/100 stars
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Accuracy of each architecture for each dataset for multiclass problem (> 90% dark, > 80% medium otherwise light).

Journal: Scientific Reports

Article Title: A comparative evaluation of deep learning approaches for ophthalmology

doi: 10.1038/s41598-024-72752-x

Figure Lengend Snippet: Accuracy of each architecture for each dataset for multiclass problem (> 90% dark, > 80% medium otherwise light).

Article Snippet: The comparison showed that there are few disadvantages to using grading over multiclass classification, especially since the accuracy is similar (85% for EfficientNet multiclass Eyepacs versus 88% for grading).

Techniques:

Original ACRIMA glaucoma image and the heatmap generated from EfficientNet.

Journal: Scientific Reports

Article Title: A comparative evaluation of deep learning approaches for ophthalmology

doi: 10.1038/s41598-024-72752-x

Figure Lengend Snippet: Original ACRIMA glaucoma image and the heatmap generated from EfficientNet.

Article Snippet: The comparison showed that there are few disadvantages to using grading over multiclass classification, especially since the accuracy is similar (85% for EfficientNet multiclass Eyepacs versus 88% for grading).

Techniques: Generated

List of architectures and accuracy (in %) of each dataset for multiclass problem.

Journal: Scientific Reports

Article Title: A comparative evaluation of deep learning approaches for ophthalmology

doi: 10.1038/s41598-024-72752-x

Figure Lengend Snippet: List of architectures and accuracy (in %) of each dataset for multiclass problem.

Article Snippet: The comparison showed that there are few disadvantages to using grading over multiclass classification, especially since the accuracy is similar (85% for EfficientNet multiclass Eyepacs versus 88% for grading).

Techniques:

Performance metrics of grading classifiers.

Journal: Scientific Reports

Article Title: A comparative evaluation of deep learning approaches for ophthalmology

doi: 10.1038/s41598-024-72752-x

Figure Lengend Snippet: Performance metrics of grading classifiers.

Article Snippet: The comparison showed that there are few disadvantages to using grading over multiclass classification, especially since the accuracy is similar (85% for EfficientNet multiclass Eyepacs versus 88% for grading).

Techniques:

Accuracy (in %) of CNN classifiers on different 2D OCT datasets.

Journal: Scientific Reports

Article Title: A comparative evaluation of deep learning approaches for ophthalmology

doi: 10.1038/s41598-024-72752-x

Figure Lengend Snippet: Accuracy (in %) of CNN classifiers on different 2D OCT datasets.

Article Snippet: The comparison showed that there are few disadvantages to using grading over multiclass classification, especially since the accuracy is similar (85% for EfficientNet multiclass Eyepacs versus 88% for grading).

Techniques: