Unrecorded-weight vision models in 2014
11
Models
9 organisations
—
Open weights
0 open, 0 closed
3
Frontier
By Epoch's flag
138M
Largest traceable
VGG16
2014
Span
2 with a traceable size
Releases
by monthOrganisation
Records
11| Model | Organisation | Released | Parameters | Weights |
|---|---|---|---|---|
| Fractional Max-Pooling | University of Warwick | 2014-12 | 27M * | Not recorded |
| Cascaded LNet-ANet | Chinese University of Hong Kong (CUHK) | 2014-11 | — | Not recorded |
| Fully Convolutional Networks | University of California (UC) Berkeley | 2014-11 | — | Not recorded |
| Deeply-supervised nets | Microsoft Research | 2014-09 | — | Not recorded |
| GoogLeNet / InceptionV1 | 2014-09 | 7M | Not recorded | |
| Spatially-Sparse CNN | University of Warwick | 2014-09 | — | Not recorded |
| VGG16 | University of Oxford | 2014-09 | 138M | Not recorded |
| VGG19 | University of Oxford | 2014-09 | 144M * | Not recorded |
| DeepFace | Tel Aviv University | 2014-06 | — | Not recorded |
| Fragment embedding | Stanford University | 2014-06 | 144M * | Not recorded |
| SPPNet | Microsoft | 2014-06 | — | Not recorded |
An asterisk marks a parameter figure the source does not consider traceable to the people who built the model. That judgement is the source’s and it has false negatives: Kimi K3 is marked speculative at 2.8T while Moonshot’s own model card states the figure. Why that distinction carries the whole exhibit.
Counts are of models Epoch AI records as notable, not of every model released. The most recent month is always incomplete, because a model enters the dataset when it is reviewed rather than when it ships.
Epoch AI, 'Data on AI Models'. Published online at epoch.ai. Retrieved from 'https://epoch.ai/data/ai-models-documentation' Used under CC BY 4.0.