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A feature recognition processor first translates the design feature model of a part into an intermediate manufacturing feature tree by handling design features according to their properties and the interacting relationships between features.
Finally, the proposed architecture is implemented in 0.13 μm CMOS technology and the fabricated chip verifies 3.2× lower energy dissipation per frame than the state-of-the-art object recognition processor.
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But an aircraft-type transponder would be too heavy for many small drones to carry, and with plastic or styrofoam airframes they might not be detected with radar.Some drone developers propose using cameras with object-recognition processors to prevent collisions.
The new Nexus smartphones will mark the start of the rollout of Google's next version of Android, which promises to extend battery life, provide more intelligent assistance features and support more advanced hardware features such as motion and voice-recognition co-processors.
In a similar vein, a collaboration with researchers at Lawrence Livermore Lab is working on increasing the speed of programs for automatic frame recognition, using inexpensive parallel processors which are commonly used for modern video gaming systems.
The AT Mega1284 was used as the processor for voice recognition and video output, two 3.5mm phone ports were set for microphones and another 3.5mm port was introduced for NTSC output.
Researchers at the University of Toronto have designed a new algorithm, which combines contextual tagging data to identify people on social media sites such as Facebook and Flickr, doing away with processor intensive facial recognition on social networks.
Notable microsystems achievements over the last 25 years include a contrast sensitive silicon retina, the first CMOS polarization sensitive imager, silicon rods in standard foundry CMOS for single photon detection, and a large scale mixed analog/digital associative processor for character recognition.
But folding the screen down activates Windows 7's Touch Pack, which includes handwriting recognition for Web browsers, word processors and other programs.
The present approach is based on a Multichannel Gradient Model (McGM) [8 10], a neuromorphic algorithm fitted to allow the construction of viable, highly robust, front-end processors for image recognition systems [11].
The main feature of this algorithm is that portions of the database (zones of interest, roadside models, and score of recognition) must be communicated between processors to accomplish the necessary treatment.
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