Determining if a deep learning model designed for computer vision will meet expectations when it is deployed is difficult and time consuming with existing tools and practices. Today, developers must run iterative experiments with command-line tools or custom scripting to identify throughput, latency and accuracy trade-offs. In this presentation, developer experience professionals at Intel will illustrate how a research and DX design process can be applied to create innovative deep learning solutions for computer vision. You'll have an opportunity to preview a design prototype that simplifies the process of performance profiling and tuning of deep learning models for use with Intel’s OpenVINO™ Toolkit. You'll also learn how your organization can apply DX best practices to improve customer experiences with your own products.
Sr. Human-Factors Engineer,
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