- Deep Learning and Digital Signal Processing: A Conversation with Cadence's Chris Rowen
- Jeff Bier’s Impulse Response—Your Autonomous Vehicle Is Ready Now…For Your Living Room
- Case Study: BDTI Expertise Enables Selection of the Best Processor for Vision Applications
- CEVA-X Processor Cores Tout DSP, Control Plane Balance for Wireless
- Texas Instruments' SoCs Aspire to Bring Advanced Driver Assistance to the Masses
April 13, 2016 | Write the first comment.
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,
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
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
March 21, 2016 | Write the first comment.
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
CEVA's DSP cores have long been a fixture in many mobile phone cellular modems, where they handle the tranceiver's digital signal processing functions, working alongside function-specific hardware accelerators. However, the physical layer coordination between the transmit and receiver
Just prior to the 2014 Consumer Electronics Show, Imagination Technologies unveiled its first computer vision processor offering with the announcement of the Raptor core architecture , the first product iteration of which was released at the February 2014 Mobile World Congress . Now, the
Automobile-based processing intelligence, both in the form of fully autonomous vehicles and more modest ADAS (Advanced Driver Assistance Systems), garnered exclusive billing in NVIDIA's keynote and booth at this year's Consumer Electronics Show, held last month in Las Vegas, Nevada. The
In 2013 , Tensilica (subsequently acquired by Cadence) released its second-generation image processing IP core, the IVP, which also supported modest computer vision capabilities ( Figure 1 ). One year later came the IVP-EP, which supported increased data precision flexibility, boosting overall
Hear the words "high volume DSP market" and you might automatically think of "mobile phones". And you'd be right; recent estimates peg quarterly worldwide mobile phone shipments approaching half a trillion units, with smartphones (which often contain multiple DSP
December 16, 2015 | Write the first comment.
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