Small Data On Cub 200 2011 30 Samples Per 1
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
模型名称 | Accuracy | Paper Title | Repository |
|---|---|---|---|
| GLICO | 77.75 | Generative Latent Implicit Conditional Optimization when Learning from Small Sample | |
| Harmonic Networks (no pre-training) | 72.26 | Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification | |
| Cross-entropy baseline (no pre-training) | 71.44 | Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification | |
| DSK Networks (no pre-training) | 71.02 | Tune It or Don't Use It: Benchmarking Data-Efficient Image Classification |
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