Low-Power

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Image-sensor maker Himax, processor core vendor CEVA, and algorithm provider emza Visual Sense have partnered to develop a low-power "always on" vision sensor module with integrated visual analytics. The three companies offered a conceptual demonstration of the product, dubbed the
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Qualcomm formally unveiled the Snapdragon 835 , its latest premium-tier mobile processor, at the Consumer Electronics Show earlier this month after a last-fall "tease" . Sporting eight CPU cores and fabricated in Samsung’s latest 10 nm process, the new chip represents the next
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At this year’s Consumer Electronics Show, I walked many miles and saw countless demos. Several of these demos were memorable, but one in particular really got my mental gears turning: Microsoft’s HoloLens. HoloLens, of course, is Microsoft’s “mixed reality”
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In March, InsideDSP covered the CEVA-X4 , the first member of the company's cellular DSP core family based on its CEVA-X architecture framework, and focused on smartphones and tablets that support gigabit-per-second LTE-Advanced and LTE-A Pro protocols. In June, the company introduced the
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Posted in Low-Power, Opinion, Video
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Based on the pace of investment and acquisitions, and the level of buzz (some would say "hype") surrounding augmented reality and virtual reality, it is obvious that these technologies are hot. With good reason, I think. Augmented and virtual reality have long held enormous
Hard on the heels of the public release of CEVA's second-generation convolutional neural network toolset, CDNN2 , the company is putting the final touches on its fifth-generation processor core, the CEVA-XM6 , designed to run software generated by that toolset. Liran Bar, the company's
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A variety of visible light- and infrared-based technologies are currently available for determining objects' locations in 3D space, as well as ascertaining their surface shapes and movements. However, these approaches sometimes come with privacy concerns; they also are unable to see inside
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We're hearing more and more about the effectiveness of deep learning for a growing range of applications. With the surge in the volume of data available for training, and reduction in the cost of computing, technologists have turned to deep neural networks for solutions to compute-intensive
Last year, when CEVA introduced the initial iteration of its CDNN (CEVA Deep Neural Network) toolset, company officials expressed an aspiration for CDNN to eventually support multiple popular deep learning frameworks. At the time, however, CDNN launched with support only for the well-known Caffe
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The general trend of recent times is toward developing DSPs that are specialized for particular "killer" applications , such as wireless or embedded vision. Many other applications also need DSPs, however, and Cadence's Tensilica Fusion DSP core family, which complements the