NVIDIA TAO Toolkit provides a low-code AI framework to accelerate vision AI model development suitable for all skill levels, from novice beginners to expert data scientists. With the TAO Toolkit, developers can use the power and efficiency of transfer learning to achieve state-of-the-art accuracy and production-class throughput in record time with adaptation and optimization.
]]>Accuracy is one of the most important metrics for deep learning models. Greater accuracy is a prerequisite for deploying the trained models to production to solve real-world problems reliably and effectively. Creating highly accurate models from scratch is time-consuming and capital-intensive. As a result, companies with limited data and resources struggle to get their AI solutions to market.
]]>To convert pixels to actionable insights, computer vision relies on deep learning to provide an understanding of the environment. Object detection is a commonly used technique to identify individual objects in a frame such as to identify people or cars. While object detection is beneficial for certain applications, it falls short when you want to understand objects at a pixel level.
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