On the afternoon of February 26th, at the G60 Science and Technology Innovation Corridor "Automotive Dynamic Vision and Radar Sensor" press conference hosted by Shanghai Baolong Automotive Technology Co., Ltd. (referred to as "Baolong Technology"), jointly organized by Shanghai Xinlun Optoelectronic Technology Co., Ltd. (referred to as "Xinlun Technology") and Wuhan University, and guided by the Songjiang District People's Government Information Office and Songjiang District Science and Technology Committee, Baolong Technology released a series of products independently developed by Baolong Technology, including dynamic vision sensors, 77G and 24G millimeter wave radars, dual current vision systems, infrared thermal imaging night vision devices, driver warning systems, and automotive facial recognition systems. This is the fusion application of artificial intelligence in the perception layer of autonomous driving. Helps cars evolve from assisted driving to autonomous driving.

Data shows that the global automotive intelligent perception field is increasingly thriving, and domestic vehicles are constantly achieving disruptive technological innovation in this field. Baolong Technology has broken through foreign technological monopolies in the perception layer sensors, opening up a new path for the safe, intelligent, and comfortable development of Chinese automobiles

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As stated by Chen Hongling, Chairman of Baolong Technology, in his speech, the company has accurately grasped the pulse of automotive intelligence development and established an automotive intelligence strategy that focuses on intelligence and control. Li Wei, Director of Automotive Electronics Unit, leads the team to strive to be the "eyes" and "ears" of automobiles.

The team integrates chip technology from Xinlun Technology and algorithm technology from Wuhan University to develop a dynamic visual sensor product with high pixel count (up to 1 million) and extremely fast response speed. It can effectively filter background and extract information, greatly reducing the complexity of backend signal processing. It can complete target recognition algorithms in the perception layer with less computing power. It can quickly and clearly display images and capture object motion trajectories in environments such as heavy fog, strong light, and weak light, making it an internationally leading visual system product.

The 77G and 24G millimeter wave radars developed by the company have strong penetration, small size, and high measurement accuracy in adverse weather conditions. They can achieve functions such as blind spot detection, traffic warning for crossing the rear of the car, and collision avoidance for the front car, helping the car operate safely and smoothly. These two technologies provide technical support for the future realization of autonomous driving in automobiles. The dynamic vision sensor chip developed by Xinlun Technology adopts the event driven principle, subverting the traditional image perception method. The underlying algorithm of image processing can be implemented on the photosensitive chip, which can directly provide useful signals for image processing after removing redundant information, greatly reducing the complexity of backend signal processing and helping artificial intelligence perceive the external world faster, more accurately, and more labor-saving. The deep learning based object detection algorithm, scene super-resolution algorithm, and object tracking algorithm independently designed by Wuhan University have outstanding performance in improving target recognition, anti-interference, and continuous stable tracking. Combined with Baolong Technology sensors, they achieve intelligent perception.

The series of automotive dynamic vision and radar sensors released this time can achieve internal control adjustment and external perception prediction in complex driving environments, providing technical support for achieving higher-level assisted driving and even autonomous driving. In addition, the product has a small size, high precision, and fast and accurate labeling, which meets the market's demand for the intelligent upgrade of the next generation of automobiles.