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CEVA Second-generation Deep Learning Toolset Supports Additional Frameworks and Topologies

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 framework, and only for a subset of possible layers and topologies based on it. The recently released second-generation CDNN2 makes notable advancements in all of these areas, including both more fully Read more...

Case Study: How to Implement Deep Learning for Vision on Embedded Processors

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 applications such as speech and image recognition, 3D object recognition, and natural language processing. Particularly where the virtually unlimited processing power and memory of cloud and enterprise Read more...

New Synopsys Processor Core Targets Traditional- and Deep Learning-based Embedded Vision

In early 2015, Synopsys' DesignWare EV5x processor core family achieved notable attention for its unique co-processor engine focused on CNNs (convolutional neural networks) for object recognition and other vision functions. The company's new EV6x processor core family includes an upgraded CNN engine that delivers substantial performance gains over its predecessor while – in a nod to customers preferring to leverage "classical" computer vision algorithms – decoupling it from the remainder of the Read more...

Tensilica Vision P6 Processor Core Adopts Deep Learning-Focused Enhancements

Just last October, Cadence announced the then-latest generation in its computer vision processor core roadmap, the Tensilica Vision P5. Only seven months later, the Vision P5 has been superseded by the Vision P6 (Figure 1). This rapid product development pace reflects the equally rapid expansion and evolution of embedded computer vision applications. According to Cadence’s Chief Technology Officer Chris Rowen and Director of Product Marketing Pulin Desai, the company's new vision core is the Read more...

Movidius' Fathom Enables Embedded Deep Learning

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 devices" was somewhat vague. However, as of earlier this month, at least some of the details of the planned collaboration become clearer, thanks to the unveiling of Movidius' Fathom Software Framework and Neural Read more...

Case Study: Growing Your Business by Targeting New Markets

One key challenge for a technology company is identifying markets for its products. Let’s say you have an idea for entering a new market using your existing technology. How do you know if there’s a fit? How do you realistically assess your risk? With more than 25 years of experience evaluating embedded processing technology, BDTI often helps clients assess and improve technology-market fit to define new products and find new markets.  BDTI understands the market trends and competitive dynamics Read more...

Deep Learning and Digital Signal Processing: A Conversation with Cadence's Chris Rowen

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, we’ve been covering deep learning concepts and implementations regularly in InsideDSP columns and news articles. Chris Rowen, Chief Technology Officer of Cadence Design Systems' IP Group, will be speaking about the Read more...

Jeff Bier’s Impulse Response—Your Autonomous Vehicle Is Ready Now…For Your Living Room

We've been hearing a lot about autonomous cars lately – and for good reasons. Driverless cars offer enormous opportunities for improved safety, convenience, and efficiency. Their proliferation may have as profound an impact on our society as conventional automobiles have had over the past century. But deploying autonomous cars widely is going to take a while, given the complexity of the application and the associated technological and regulatory challenges. In the meantime, autonomous vehicles Read more...

Case Study: BDTI Expertise Enables Selection of the Best Processor for Vision Applications

With more and more products incorporating computer vision functionality, semiconductor vendors are increasingly designing specialized processors for vision applications. For product developers, this means that identifying the best processor (whether a chip for use in a system design, or an IP core for use in an SoC) is challenging—for several reasons. First, processors for vision vary greatly in their architectures, making them tough to compare. Second, there is no universal set of benchmarks Read more...

Texas Instruments' SoCs Aspire to Bring Advanced Driver Assistance to the Masses

ADAS (advanced driver assistance systems) are rapidly being incorporated into automobiles and other vehicles, as products unveiled at January's North American International Auto Show in Detroit, Michigan made clear. Just a few short years ago, passive collision warning and active collision avoidance features were restricted to luxury models from luxury manufacturers. Now, even mass-market car suppliers are incorporating ADAS capabilities into their high-end and mainstream vehicles. In order for Read more...