Boe Technology Group Co., Ltd.

Chinese Academy of Sciences

Beijing Sensetime Technology Development Co., Ltd.

Beijing Tusen Zhitu Technology Co., Ltd.

Hongyang Li

Xin Li

Yu Liu

Xiangxiang Zou

Naifu Wu

Xiaogang Wang

Zhe Zhang

Naiyan Wang

Shuai Yang

Xiangdong Yang

Wanli Ouyang

Zehao Huang

Sujia Jiang

Youlong Wang

Meng Peng

Jialin Wei

Xuhui Wen

Embodiments of the present invention disclose a binocular image matching method, apparatus, device, and storage medium. The method comprises: performing target detection on a first image to obtain a first bounding box of a target in the first image; determining a second bounding box corresponding to the first bounding box in a second image; and obtaining a third bounding box of the target in the second image by regressing the second bounding box. The technical solutions realize accurate matching of targets in a binocular image without requiring performing target detection on both images in the binocular image, and then use a matching algorithm to match the targets detected in the two images, thereby greatly reducing the calculation overhead of target matching in the binocular image.

Binocular image matching method, device, and storage medium

An information synchronization method, a terminal and a system, which relates to the technical field of communication. The method includes: by the first terminal, sending a controlling request of a target terminal to the controlling server; by the first terminal, receiving a state feedback information sent by the first terminal, according to the state feedback information, updating an information of the first terminal; and by the first terminal, sending the state feedback information to each of the at least one second terminal, so that the second terminal updates an information of the second terminal according to the state feedback information.

Information synchronization method, terminal and information synchronization system

An object detection method, a neural network training method, an apparatus, and an electronic device include: obtaining, through prediction, multiple fused feature graphs from images to be processed, through a deep convolution neural network for target region frame detection, obtaining multiple first feature graphs from a first subnet having at least one lower sampling layer, obtaining multiple second feature graphs from a second subnet having at least one upper sampling layer, and obtaining fused graph by fusing multiple first feature graphs and multiple second feature graphs respectively; and obtaining target region frame data according to the multiple fused feature graphs. Because the fused feature graphs better represent semantic features on high levels and detail features on low levels in images, target region frame data of big and small objects in images can be effectively extracted according to the fused feature graphs, thereby improving accuracy and robustness of object detection.

Method and apparatus for detecting object, method and apparatus for training neural network, and electronic device

A control method for a series hybrid power system or synergic electric power supply and a control device thereof are disclosed. The control device includes: a generator reference current value generating module and a generator current control module. The generator reference current value generating module is configured to generate a reference current value of a generator according to an actual current value of an energy storage device, a reference current value of the energy storage device, an actual voltage value of a DC bus, and a reference voltage value of the DC bus. The generator current control module is configured to generate a control signal of a rectifier according to the reference current value of the generator, the actual value of any two-phase current of the generator, and an actual angular velocity of the generator, thereby controlling the series hybrid power system or the synergic electric power supply.

Control method for series hybrid power system or synergic electric power supply and control device thereof

The present disclosure relates to a user identification method applicable to a vehicle, the vehicle including at least two microphone arrays, the respective microphone arrays being disposed at different positions of the vehicle, respectively. The user identification method includes: receiving a voice of a user within the vehicle through the at least two microphone arrays; determining directions from the user to the microphone arrays, respectively, according to the voice; calculating an angle between any two of the directions; and identifying a type of the user based at least on the angle.

User identification method and user identification apparatus

Growing community of inventors

Beijing, China

Hongyang Li