Lattice Semiconductor to Host the Vision Industry and Technology Forum – Presented by the Embedded Vision Alliance

Lattice Semiconductor Corporation (NASDAQ: LSCC) has announced that as part of its investment in smart vision systems, it will host the upcoming Vision Industry and Technology Forum, a quarterly invitation-only event presented by the Embedded Vision Alliance®. The Forum will be held at Lattice’s Silicon Valley Development Center in San Jose, California on Wednesday, January 30th, 2019. Computer vision, also called visual AI, is the use of digital processing and intelligent algorithms to interpret meaning from images or video. Computer vision has mainly been a field of academic research over the past several decades. Today, however, a major transformation is underway. Due to the emergence of very powerful, low-cost, and energy-efficient processing, it has become possible to incorporate practical computer vision capabilities into embedded systems, mobile devices, PCs, and the cloud. Over the next few years, there will be a rapid proliferation of vision technology into many kinds of systems. “As an active member of the Embedded Vision Alliance, Lattice is committed to enabling the growth of flexible, low power embedded vision technology through innovative solutions such as Video Interface Platform and Lattice sensAI™ stack. The Vision Industry and Technology Forum brings together distinguished speakers and invited audience drawn from the Alliance’s more than 90 member companies, and Lattice is honoured to host and participate in this important Forum,” said Deepak Boppana, Sr. Director Segment and Solutions Marketing. Presentation topics include: New results from the Alliance’s 2018 Computer Vision Developer Survey. Deploying computer vision at scale to reduce the risk of older patients falling in hospitals and other healthcare settings. Using computer vision at the edge to allow vehicle fleet operators to monitor and improve the safety of their drivers. Unique perspectives and data on fundamental trends in ADAS and autonomous vehicles. New approaches to enabling the automated design of computationally efficient deep neural networks.

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