There is a lot of video in the world. Nearly 90% of global internet traffic is video. Getting value out of video data, however, is challenging, time-consuming and expensive. How do you identify the right subset of video data to train your models, and how do you reimagine the annotation process to accelerate vision AI application development are just some of the big questions that are looking for answers. On this episode of the AI in Automotive Podcast, I am delighted to be joined by Dr Jason ...
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There is a lot of video in the world. Nearly 90% of global internet traffic is video. Getting value out of video data, however, is challenging, time-consuming and expensive. How do you identify the right subset of video data to train your models, and how do you reimagine the annotation process to accelerate vision AI application development are just some of the big questions that are looking for answers. On this episode of the AI in Automotive Podcast, I am delighted to be joined by Dr Jason ...
There has been a lot of talk recently about vision versus LiDARs and RADARs. I hosted Leaf Jiang, CEO of a company called NODAR to learn more about the advantages and limitations of each technology, and how NODAR's own technology overcomes them. Their name is a nice play on the fact that their product is not RADAR or LiDAR, but in fact, uses vision to achieve resolution and depth perception better than either of them. Instead of relying on machine learning models to interpret the feed from th...
AI in Automotive Podcast
There is a lot of video in the world. Nearly 90% of global internet traffic is video. Getting value out of video data, however, is challenging, time-consuming and expensive. How do you identify the right subset of video data to train your models, and how do you reimagine the annotation process to accelerate vision AI application development are just some of the big questions that are looking for answers. On this episode of the AI in Automotive Podcast, I am delighted to be joined by Dr Jason ...
