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Kyocera develops GaN laser-based night vision system

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Solution combines RGB-NIR sensors and AI technology for better visibility at night and in bad weather

Kyocera has developed an automotive night vision system that can accurately identify collision-risk objects in low-visibility driving conditions, such as at night, or in rain, snow, fog, or smoke.

Designed to reduce traffic accidents and promote safer driving, it features what is thought to be the first headlight that can emit both white (RGB) and near-infrared (NIR) light on the same optical axis; this allows higher accuracy object recognition than alternative technologies. The technology uses white and NIR diodes Integrated into a single GaN laser device, developed by Kyocera SLD Laser Inc.

The integrated system has automatic beam shaping functionality for the RGB and NIR light that prevents glare for oncoming drivers by automatically shifting visible light into a low-beam pattern when necessary, while the NIR light can remain in high-beam mode.

The system uses 'Image-Fusion AI Recognition Technology' developed by Kyocera for object recognition. Instead of simply combining the image data from the two sources, Kyocera's system uses qualitative AI to compare and assess both RGB and NIR images, differentiating between pedestrians and vehicles with high accuracy even in low visibility conditions.

In addition, Kyocera has developed a way to create training data more easily. Conventional methods require collection of vast amounts of NIR training data, a time-consuming and costly process. Kyocera's AI technology generates training data automatically. As a result, this approach can reduce training costs while maintaining high accuracy in recognition performance, according to the company.

Kyocera will continue R&D for this system, aiming for commercialisation after 2027.

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