Shenzhen University

Zhongming Liang

Jianqiang Li

Fei Yu

Jie Chen

Jia Wang

HaiJun Zhang

Song Guo

Qinjian Li

Luya Wang

Yanjie Dong

Shuqing Hu

Disclosed are a method, an apparatus, a device, and a medium for image recognition via wireless federated learning. The method for image recognition via wireless federated learning includes: obtaining an image to be recognized and an initial image recognition model; adjusting parameters for the initial image recognition model via a preset accelerated mobile federated learning algorithm according to a target momentum factor to obtain a target image recognition model; and recognizing the image to be recognized through the target image recognition model to obtain text information corresponding to the image to be recognized.

Method, apparatus, device, and medium for image recognition via wireless federated learning

The present provides a visual positioning method and system based on a Gaussian process and a storage medium. The method includes: collecting image of surrounding environment and moving trajectory points while traveling (S); extracting global features and semantic features from images (S); processing the extracted global features and semantic features and the moving trajectory points according to a preset processing rule to obtain a Gaussian process observation model (S); and reconstructing a Bayes filtering framework according to the Gaussian process observation model, endowing a current trajectory with an initial position point, and generating a next position point of the current trajectory, the next position point being used for providing a positioning guidance for navigation (S). An association between a current state and a historical state can be established, so that the accuracy of a predicted next position point is improved, and accurate navigation can be provided for a robot motion.

Visual positioning method and system based on Gaussian process, and storage medium

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Shenzhen, China

Zhongming Liang