Software Development

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
Modern SoCs increasingly contain a variety of processing resources: one or more CPU cores and a GPU, often with a DSP, programmable logic, or one or multiple special-purpose co-processors for tasks such as computer vision. Properly harnessed, such heterogeneous processors often deliver impressive
In late January of this year, Movidius and Google broadened their collaboration plans, which had begun with 2014's Project Tango prototype depth-sensing smartphone . As initially announced , the companies’ broader intention to "accelerate the adoption of deep learning within mobile
Convolutional neural networks (CNNs) and other "deep learning" techniques are finding increasing use in a variety of detection and recognition tasks:  identifying music clips and speech phrases, for example, and finding human faces and other objects in images and videos. As a result,
As computer vision is deployed into a variety of new applications, driven by the emergence of powerful, low-cost, and energy-efficient processors, companies need to find ways to squeeze demanding vision processing algorithms into size-, weight-, power, and cost-constrained systems. Fortunately for
Algorithms are the essence of digital signal processing; they are the mathematical "recipes" that transform signals in useful ways. Companies developing new algorithms, or considering purchasing or licensing algorithms, often need to assess whether an algorithm will fit within their
As applications become more complex, and processors become more powerful, system developers increasingly rely on off-the-shelf software components to enable rapid and efficient application development. This is particularly true in digital signal processing, where application developers expect to
As Jeff Bier has mentioned in several of his recent columns, deep learning algorithms have gained prominence in computer vision and other fields where there's a need to extract insights from ambiguous data. Convolutional neural networks (CNNs) – massively parallel algorithms made up of
It's becoming increasingly possible, thanks to APIs and languages such as Khronos' OpenCL , for applications to efficiently harness the heterogenous computing resources available in modern SoCs. And it's therefore increasingly common for SoC designers to include a variety of both
Today's smartphones are technological marvels that deliver an extraordinary range of capabilities from GPS-based navigation to sophisticated photography. But sometimes we just want to make a phone call. And particularly when we're on the move, who hasn't struggled to hear the other