efficientnet b3 scales Search Results


efficientnet b3 scales  (Kaggle Inc)
86
Kaggle Inc efficientnet b3 scales
Overview of the proposed pipeline. Each fundus image is preprocessed to produce a vessel-enhanced image and a morphological skeleton for persistent <t>homology.</t> <t>EfficientNet-B3</t> provides 1536-d CNN features; TDA yields six topological descriptors concatenated to form augmented node representations. A topology-aware population graph connects similar images; two-layer GraphSAGE refines representations through neighbourhood aggregation for five-class DR grading.
Efficientnet B3 Scales, 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/result/efficientnet b3 scales/product/Kaggle Inc
Average 86 stars, based on 1 article reviews
efficientnet b3 scales - by Bioz Stars, 2026-06
86/100 stars
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resnet18-softmax  (SoftMax Inc)
90
SoftMax Inc resnet18-softmax
Overview of the proposed pipeline. Each fundus image is preprocessed to produce a vessel-enhanced image and a morphological skeleton for persistent <t>homology.</t> <t>EfficientNet-B3</t> provides 1536-d CNN features; TDA yields six topological descriptors concatenated to form augmented node representations. A topology-aware population graph connects similar images; two-layer GraphSAGE refines representations through neighbourhood aggregation for five-class DR grading.
Resnet18 Softmax, supplied by SoftMax 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/resnet18-softmax/product/SoftMax Inc
Average 90 stars, based on 1 article reviews
resnet18-softmax - by Bioz Stars, 2026-06
90/100 stars
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Image Search Results


Overview of the proposed pipeline. Each fundus image is preprocessed to produce a vessel-enhanced image and a morphological skeleton for persistent homology. EfficientNet-B3 provides 1536-d CNN features; TDA yields six topological descriptors concatenated to form augmented node representations. A topology-aware population graph connects similar images; two-layer GraphSAGE refines representations through neighbourhood aggregation for five-class DR grading.

Journal: bioRxiv

Article Title: A graph-based deep learning framework for diabetic retinopathy classification with topology-aware feature augmentation

doi: 10.64898/2026.03.19.713075

Figure Lengend Snippet: Overview of the proposed pipeline. Each fundus image is preprocessed to produce a vessel-enhanced image and a morphological skeleton for persistent homology. EfficientNet-B3 provides 1536-d CNN features; TDA yields six topological descriptors concatenated to form augmented node representations. A topology-aware population graph connects similar images; two-layer GraphSAGE refines representations through neighbourhood aggregation for five-class DR grading.

Article Snippet: Feature extraction with EfficientNet-B3 scales linearly as O ( N ); for N = 88,702 (Kaggle DR), this requires ≈7 min on a single A100 GPU.

Techniques: