Image recognition SoC integrates deep neural network accelerator

February 27, 2019 //By Christoph Hammerschmidt
Image recognition SoC integrates deep neural network accelerator
Autonomous driving requires rather sophisticated sensors – and these sensors deliver much higher amounts of data than available ones. To meet the need for more powerful image processing, Toshiba Electronics Europe (TEE) has announced an image recognition SoC with an integrated deep learning accelerator. The result: Up to ten times faster image recognition and four times better power efficiency in comparison to the company’s previos product. Details of the technology were reported at the 2019 IEEE International Solid-State Circuits Conference (ISSCC) in San Francisco.

Advanced driver assistance systems, such as autonomous emergency braking, offer increasingly advanced capabilities, and implementing them requires image recognition SoC that can recognize road traffic signs and road situations at high speed with low power consumption.

Deep neural networks (DNN), algorithms modeled after the neural networks of the brain, perform recognition processing much more accurately than conventional pattern recognition and machine learning, and is widely expected to find utilization in automotive applications. However, DNN-based image recognition with conventional processors takes time, as it relies on a huge number of multiply-accumulate (MAC) calculations. DNN with conventional high-speed processors also consumes too much power.


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