Automobile

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Self Driving Vechicles

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Autonomous driving scenarios require the car to quickly and accurately recognize the surrounding objects and environment, but this is difficult to achieve with traditional Computer Vision programs, but deep learning can. Thanks to the development of deep learning, autonomous driving has never been so close to us.
face recognition while driving

For the commonly used Advanced Driving Assistance System(ADAS), it is also necessary to detect the driver’s physical condition and emotional fluctuations, which can avoid traffic accidents caused by fatigue driving and extreme emotions. As for the detection of the driver’s physical condition and mood fluctuations, conventional sensors cannot meet the requirements of high accuracy and robustness, which will lead to inaccurate judgments.

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Apart from that, as the driving scene is very complex, the design of the deep learning model is difficult to fully test. Therefore, for deep learning, a set of high-precision and robust testing tools including safety monitoring, system testing, and anomaly detection is very important.

Our Solution

Key Milestones Of Waymo Googles Self Driving Cars

COEUS provides a series of solutions including high-precision sensors, embedded model, deep learning model testing, system testing, and real-time monitoring with anomaly detection to achieve full driving scene coverage and further improve the accuracy and robustness of the detection of the driver’s physical condition and mood fluctuations. Complete model testing and anomaly detection solutions: Coeustech focuses on deep learning model testing, and can combine existing traffic rules and model testing technologies to automatically test whether the model’s performance under various road conditions meets legal compliance. At the same time, the anomaly detection module provided by Coeustech will also conduct real-time monitoring of the model when the vehicle is running, so as to protect your safety.

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