Beijing Didi Infinity Technology and Development Co., Ltd.

Pivotal Software, Inc.

Vimicro Corporation

The Procter Gamble Company

Tencent Technology Company Limited

Yuan Zhao

Lei Zhu

Hongsing Tan

Rui Shen

Haifeng Shen

Xiaoming Gao

Ning Fu

Shuai Tan

Zhengjun Zhou

Jianze Ma

Junchao Chen

Wa Ye

Yuxuan Zhang

Yuehai Chen

Paul R Mort Iii

Embodiments of the disclosure provide a method for detecting an inter-person conflict. The method includes receiving at least one image from an image data resource, where the at least one image is captured by at least one camera. The method further includes detecting human objects from the at least one image. The method additionally includes determining a distance between two of the detected human objects. The method additionally includes determining whether there is a conflict between the two of the detected human objects based on the determined distance.

System and method for detecting in-vehicle conflicts

Embodiments of the disclosure provide a system for detecting a conflict in a vehicle. The system includes at least one camera, which is configured to capture a plurality of images in the vehicle. The system further includes a controller in communication with the at least one camera. The controller is configured to detect human objects from the plurality of images, estimate depth information of the respective human objects, and detect the conflict based on the depth information.

A method for using a structurally more complicated reference model to train a structurally simpler learner model includes: obtaining a trained reference model at least including N reference blocks and a learner model at least including N learner blocks respectively corresponding to the N reference blocks; training the learner model by conducting an iterative operation; determining whether the learner model is convergent; and in response to that the learner model is convergent, stopping the iterative operation to assign the learner model as a trained learner model. The iterative operation includes inputting a sample data set into the trained reference model and the learner model; for each of the N learner blocks: determining a distance between a learner vector of the learner block and a reference vector of the reference block, and updating parameters in the learner block based on the determined distance.

Artificial intelligent systems and methods for using a structurally simpler learner model to mimic behaviors of a structurally more complicated reference model

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributed data management. One of the methods includes converting a standard specification for a software package into a custom specification for a software deployment tool that deploys the software package on one or more distributed computing systems, parsing source files and corresponding configuration files to determine configuration parameters and custom values, writing the determined configuration parameters into a custom template, and updating the custom specification with the determined custom values for the configuration parameters and information associated with the custom template.

Fast deployment across cloud platforms

Techniques for a simple file system for facilitating file transmission are disclosed. According to one aspect of the techniques, a storage device comprises a memory, a creation module, a status record module and a data reading/writing module. The creation module creates a parameter block, a file allocated table, a root directory and a data area in the memory. The starting address of the data area is calculated according to parameters in the parameter block. The status record module stores a last writing address of a last writing access to the memory. The data reading/writing module reads data from the data area according to the starting address and the last writing address.

Device for transmitting data and method for the same

Growing community of inventors

Beijing, China

Yuan Zhao