Baidu USA LLC

Baidu.com Times Technology (beijing) Co. Ltd.

Zhisheng Hu

Zhenyu Zhong

Kang Li

Xinyang Zhang

Shengjian Guo

Provided are a data processing method and apparatus, an electronic device, and a medium, and relates to the technical field of computers, and in particular to the field of autonomous driving and intelligent transportation. An implementation is: obtaining risk information in driving scenario data of a driving scenario; determining a risk factor set based on the risk information, where the risk factor set includes a risk factor existing in the driving scenario data; and generating a simulated risk scenario based on the risk factor set, where the simulated risk scenario reflects at least one risk factor in the risk factor set.

Data processing

The disclosure describes various embodiments for detecting an unexpected control state of an autonomous driving system. According to an embodiment, an exemplary method of detecting an unexpected control state of an autonomous driving system include the operations of generating environmental data of a vehicle; determining, by the autonomous driving system, a first control state based on the environmental data of the vehicle; determining, by a reference model, a second control state based on the environmental data, wherein the reference model defines at least one scenario each corresponding to a plurality of expected control states and a state switching condition, and in each of the expected control states corresponding to the scenario, an action of the vehicle in the scenario obeys a traffic rule; and determining the unexpected control state of the autonomous driving system by comparing the first control state with the second control state.

Method and apparatus for detecting unexpected control state in autonomous driving system

The present disclosure provides an image processing method and apparatus, an electronic device and a storage medium, which relate to the field of computer technology, and more particularly to artificial intelligence technology including computer vision, deep learning and the like. The image processing method includes: recognizing the image to be processed to determine attribute information of each object included in the image to be processed; determining a target thermal image to be recognized according to the attribute information of each object and the image to be processed; reconstructing the target thermal image to generate a first reconstructed image; and determining whether the image to be processed includes an object of a preset class according to a difference between the first reconstructed image and the target thermal image.

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Sunnyvale, CA, United States of America

Zhisheng Hu