C-SVDDNet

Reported on 2 benchmarks across 1 task · 1 paper

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

Computer Vision2 results

Image ClassificationonMNIST
Percentage error· 2014-12-23
0.4
best: 0.13 (Branching/Merging CNN + Homogeneous Vector Capsules)
Unsupervised Feature Learning with C-SVDDNet arXiv:1412.7259
Image ClassificationonSTL-10
Percentage correct· 2014-12-23
68.2
best: 99.64 (µ2Net+ (ViT-L/16))
Unsupervised Feature Learning with C-SVDDNet arXiv:1412.7259