公开(公告)号：US11328180B2

公开(公告)日：2022-05-10

申请号：US16666631

申请日：2019-10-29

Applicant: Beijing Horizon Robotics Technology Research and Development Co., Ltd.

Inventor： Yonghao Xu ,  Qian Zhang ,  Guoli Wang ,  Chang Huang

IPC: G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: Disclosed are a method for updating a neural network and an electronic device. The method includes: inputting a first image set having tag information into a first depth neural network, and determining a cross entropy loss value of the first image set by using the first depth neural network; inputting a second image set having no tag information separately into the first depth neural network and a second depth neural network, and determining a consistency loss value of the second image set, the first depth neural network and the second depth neural network having the same network structure; updating parameters of the first depth neural network based on the cross entropy loss value and the consistency loss value; and updating parameters of the second depth neural network based on the updated parameters of the first depth neural network.

公开(公告)号：US11195098B2

公开(公告)日：2021-12-07

申请号：US16666344

申请日：2019-10-28

Applicant: Beijing Horizon Robotics Technology Research and Development Co., Ltd.

Inventor： Yukang Chen ,  Qian Zhang ,  Chang Huang

IPC: G06N3/08 ,  G06K9/62 ,  G06N20/20 ,  G06N3/04

Abstract: Disclosed are a method for generating a neural network, an apparatus thereof, and an electronic device. The method includes: obtaining an optimal neural network and a worst neural network from a neural network framework by using an evolutionary algorithm; obtaining an optimized neural network from the optimal neural network by using a reinforcement learning algorithm; updating the neural network framework by adding the optimized neural network into the neural network framework and deleting the worst neural network from the neural network framework; and determining an ultimately generated neural network from the updated neural network framework. In this way, a neural network is optimized and updated from a neural network framework by combining the evolutionary algorithm and the reinforcement learning algorithm, thereby automatically generating a neural network structure rapidly and stably.

公开(公告)号：US11037031B2

公开(公告)日：2021-06-15

申请号：US16788661

申请日：2020-02-12

Applicant: Beijing Horizon Robotics Technology Research and Development Co., Ltd.

Inventor： Chaoxu Guo ,  Qian Zhang ,  Guoli Wang ,  Chang Huang

IPC: G06K9/62 ,  G06N3/04

Abstract: An image recognition method includes: determining a first feature map of the current frame image by using a convolutional neural network based on a type of a current frame image; determining a second feature map of a key frame image before the current frame image; performing feature alignment on the first feature map and the second feature map to obtain a first aligned feature map; fusing the first feature map and the first aligned feature map to obtain a first fused feature map; and recognizing content in the current frame image based on the first fused feature map.