DECEMBER - JANUARY8 IN MY OPINIONNeomar GiacominiHOW TO PREPARE FOR THE FUTURE OF MACHINE VISIONBY PAUL CHEN, HEAD OF GLOBAL ELECTRONICS, MATTEL [NASDAQ: MAT]Over the past decade, the promise of machine vision has undeniablytaken off. From self-driving cars all the way to facial recognition doorbells, the applications have captured the imagination of the public. To get these solutions right and be where we are today,a massive amount of work was required on the embedded infrastructure. As a developer of products, I find it exciting to see the industry continue tolearn and evolve in a scalable way as the demand for machine vision has grown. I would like to share three current trends in this space: 1: Levels of recognition.Often, we get requests to "recognize" an object or people. Recognition has a wide span of meanings. First, thereis the deep learning/machine learning level of recognition driven by the real-time needs of self-driving, facial-based identity, and instant awareness of a large number of objects. Figure 1's upper-right quadrant represents this well, and is an area that many are calling ubiquitous in commercial and industrial applications.Paul Chen
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