AI models
Vision-based obstacle avoidance system (2005)
Parameters
72K
Published
Dec 5, 2005
Vision-based obstacle avoidance system (2005) is an AI model developed by New York University (NYU), Net-Scale technologies and NEC Laboratories (United States), first published in December 2005. It works in the robotics and vision domain, on tasks such as self-driving car and object detection.
Epoch AI has no training-compute estimate for this model. The model has 72,000 parameters. Training ran on 1 Intel Pentium 4 HT 630 for about 96 hours.
Access: Unreleased. Its weights are not openly released. The reference paper has 742 citations. Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- New York University (NYU), Net-Scale technologies, NEC Laboratories
- Country of organization
- United States
- Domain
- Robotics, Vision
- Task
- Self-driving car, Object detection
- Parameters
- 72,000
- Training hardware
- Intel Pentium 4 HT 630
- Chips used
- 1
- Training time
- 96 h
- Training power draw
- 103 W
- Model accessibility
- Unreleased
- Open weights
- No
- Citations
- 742
- Epoch confidence
- Confident
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.
← All ai models