公开(公告)号：US20220343662A1

公开(公告)日：2022-10-27

申请号：US17861741

申请日：2022-07-11

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Yuning DU ,  Yehua YANG ,  Chenxia LI ,  Qiwen LIU ,  Xiaoguang HU ,  Dianhai YU ,  Yanjun MA ,  Ran BI

IPC: G06V30/14 ,  G06V10/82 ,  G06V30/19

Abstract: The present disclosure provides a method and apparatus for recognizing a text, a device and a storage medium, and relates to the field of deep learning technology. A specific implementation comprises: receiving a target image; performing a text detection on the target image using a pre-trained lightweight text detection network, to obtain a text detection box; and recognizing a text in the text detection box using a pre-trained lightweight text recognition network, to obtain a text recognition result.

公开(公告)号：US20220247626A1

公开(公告)日：2022-08-04

申请号：US17718149

申请日：2022-04-11

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Cheng CUI ,  Tingquan GAO ,  Shengyu WEI ,  Yuning DU ,  Ruoyu GUO ,  Bin LU ,  Ying ZHOU ,  Xueying LYU ,  Qiwen LIU ,  Xiaoguang HU ,  Dianhai YU ,  Yanjun MA

IPC: H04L41/0806 ,  H04L41/084 ,  H04L41/0894 ,  G06K9/62

Abstract: The present disclosure provides a method for generating a backbone network, an apparatus for generating a backbone network, a device, and a storage medium. The method includes: acquiring a set of a training image, a set of an inference image, and a set of an initial backbone network; training and inferring, for each initial backbone network in the set of the initial backbone network, the initial backbone network by using the set of the training image and the set of the inference image, to obtain an inference time and an inference accuracy of a trained backbone network in an inference process; determining a basic backbone network based on the inference time and the inference accuracy of the trained backbone network in the inference process; and obtaining a target backbone network based on the basic backbone network and a preset target network.

公开(公告)号：US20210209471A1

公开(公告)日：2021-07-08

申请号：US17211146

申请日：2021-03-24

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Haifeng WANG ,  Xiaoguang HU ,  Dianhai YU

IPC: G06N3/08 ,  G06N3/063 ,  G06F7/76

Abstract: The present application discloses a processor video memory optimization method and apparatus for deep learning training tasks, and relates to the technical field of artificial intelligence. In the method, by determining an optimal path for transferring a computing result, the computing result of a first computing unit is transferred to a second computing unit by using the optimal path. Thus, occupying the video memory is avoided, and meanwhile, a problem of low utilization rate of the computing unit of a GPU caused by video memory swaps is avoided, so that training speed of most tasks is hardly reduced.