AI models
ConvNet Processor
Training compute
3.1×10¹⁴ FLOP
Parameters
14.4K
Published
Aug 31, 2009
ConvNet Processor is an AI model developed by Courant Institute of Mathematical Sciences (United States), first published in August 2009. It works in the vision domain, on tasks such as face detection.
Training it took an estimated 3.1×10¹⁴ FLOP of compute (estimation method: operation counting). The model has 14,423 parameters. It was trained on roughly 30K datapoints.
Access: Unreleased. Its weights are not openly released. Epoch AI rates the confidence of this record as likely.
Full record
- Organization
- Courant Institute of Mathematical Sciences
- Country of organization
- United States
- Domain
- Vision
- Task
- Face detection
- Training compute
- 3.1×10¹⁴ FLOP
- Compute estimation method
- Operation counting
- Parameters
- 14,423
- Dataset size
- 30K
- Model accessibility
- Unreleased
- Open weights
- No
- Epoch confidence
- Likely
More from Courant Institute of Mathematical Sciences
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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