UCSD & Microsoft Improve Image Recognition With Extremely Low FLOPs
A research team from the University of California San Diego and Microsoft has come up with a novel approach to improve model accuracy on computer vision tasks at extremely low compute costs, achieving significant performance gains over state-of-the-art models.
A research team from the University of California San Diego and Microsoft has come up with a novel approach to improve model accuracy on computer vision tasks at extremely low compute costs, achieving significant performance gains over state-of-the-art models.
computer vision tasks, low compute costs, significant performance gains, research team, San Diego, novel approach, model accuracy, art models, university, California, Microsoft
