Image Classification On Malaria Dataset
Metrics
Acc. (test)
PARAMS
Results
Performance results of various models on this benchmark
Model Name | Acc. (test) | PARAMS | Paper Title | Repository |
|---|---|---|---|---|
| kEffNet-B0 V2 16ch | 97.61% | 0.61M | An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints | |
| µ2Net+ (ViT-L/16) | 97.46% | - | A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems | |
| kEffNet-B0 V2 2ch | 96.70% | 0.3M | An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility Constraints |
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