AI models
DenseNet-264
Parameters
34M
Published
Aug 25, 2016
DenseNet-264 is an AI model developed by Tsinghua University, Facebook AI Research and Cornell University (China, United States and France), first published in August 2016. It works in the vision domain, on tasks such as image classification.
Epoch AI has no training-compute estimate for this model. The model has 34,000,000 parameters.
Access: Open weights (unrestricted). Its weights are openly available. The reference paper has 43,094 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- Tsinghua University, Facebook AI Research, Cornell University
- Country of organization
- China, United States, France
- Domain
- Vision
- Task
- Image classification
- Parameters
- 34,000,000
- Model accessibility
- Open weights (unrestricted)
- Open weights
- Yes
- Citations
- 43,094
- Epoch confidence
- Confident
More from Tsinghua University,Facebook AI Research,Cornell University
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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