Toshiba Electronic Devices & Storage Corporation (“Toshiba”) today announced the development of Deep Neural Network (DNN [1]) hardware IP[2] that will help to realize advanced driver assistance systems (ADAS) and autonomous driving functions. The company will integrate the DNN hardware IP with conventional image processing technology and start sample shipments of ViscontiTM5, the next generation of Toshiba’s image-recognition processor, in September 2019.
The DNN hardware IP draws on deep learning to deliver more accurate detection and identification of a wider range of objects than image recognition based on conventional pattern recognition and machine learning. It enables ViscontiTM5 to recognize road traffic signs and road situations at high speed with low power consumption.
Toshiba will promote ViscontiTM5 equipped with DNN hardware IP as a key component of next-generation advanced driver assistance systems.
Advanced driver assistance systems such as autonomous emergency braking are now being widely adopted, from luxury cars to subcompacts. They are also expected to offer increasingly advanced capabilities – for instance, the 2020 version of the influential European New Car Assessment Programme (Euro NCAP), the EU-backed safety standard, adds testing to avoid collisions at intersections. This trend will increase the demand for more advanced and capable systems.
Toshiba Electronic Devices & Storage Corporation will continue to develop the Visconti™ family and contribute to traffic safety.
Outline of ViscontiTM5
| Product Series Name | TMPV770 series |
| CPU core | Arm® Cortex®-A53 |
| Arm® Cortex®-R4 processor with Floating Point Unit | |
| Image processing DSP | General DSP |
| Image Processing Accelerator | Affine conversion |
| Pyramid Image Generator | |
| Enhanced CoHOG Feature-based Support Vector Machine | |
| Dense Optical Flow | |
| Template Matching | |
| Dense Stereo Matching | |
| Deep Neural Network | |
| Image Signal Processor | |
| Video input interface | MIPI CSI-2 RX |
| Video output interface | MIPI CSI-2 TX |
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