In our 2nd public research challenge contestants were faced with using deep learning to solve for a vehicle detection algorithm that can adapt to change. Researchers worldwide got to test their skills, win prizes (1st place $5,000, 2nd place $2,000, 3rd place $1,000), and join our mission
Also introducing our latest data challenge for autonomous developers [https://www.getnexar.com/challenge-2/]` It could be argued there is only one proven Big Data application — web search. Nothing so far has met the sheer size and complexity of indexing the web at the precision, recall, and freshness Google delivers.
Edge devices and very large real-world driving datasets hold the promise of autonomous driving Over the past few years, we’ve seen significant advances in learning-based approaches to the development of automotive safety applications. These advances have been applied predominantly to the perception stage of autonomous driving systems. The decisioning
We challenged researchers with teaching deep networks to identify traffic lights, and now they share what they learned in the process. Read on for their insights and a look at their open-source models. Deep learning plays a key role in the race to autonomous vehicles and we wanted to open
Introducing NEXETNexar recently released the largest and most diverse automotive road dataset for researchers in the world. We’d like to provide some context on the evolution of autonomous driving perception and why we’re giving everyone access to our data. For 30 years, neural networks have been the black