WRN + Self-Organizing Map

Reported on 4 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision4 results

Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2020-09-04
82.2
best: 98.72 (SgVA-CLIP)
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning arXiv:2009.03665
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2020-09-04
71.5
best: 97.95 (SgVA-CLIP)
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning arXiv:2009.03665
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· 2020-09-04
82.2
best: 98.72 (SgVA-CLIP)
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning arXiv:2009.03665
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· 2020-09-04
71.5
best: 97.95 (SgVA-CLIP)
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning arXiv:2009.03665