-
公开(公告)号：US11640550B2
公开(公告)日：2023-05-02
申请号：US16026976
申请日：2018-07-03
Inventor： Lan Liu , Faen Zhang , Kai Zhou , Qian Wang , Kun Liu , Yuanhao Xiao , Dongze Xu , Tianhan Xu , Jiayuan Sun
Abstract: The disclosure discloses a method and apparatus for updating a deep learning model. An embodiment of the method comprises: executing following updating: acquiring a training dataset under a preset path, training a preset deep learning model based on the training dataset to obtain a new deep learning model; updating the preset deep learning model to the new deep learning model; increasing training iterations; determining whether a number of training iterations reaches a threshold of training iterations; stopping executing the updating if the number of training iterations reaches the threshold of training iterations; and continuing to execute the updating after an interval of a preset time length if the number of training iterations fails to reach the threshold of training iterations. This embodiment has improved the model updating efficiency.
-
公开(公告)号：US11310559B2
公开(公告)日：2022-04-19
申请号：US16255725
申请日：2019-01-23
Inventor： Hang Jiang , Minghao Liu , Yang Liang , Shuangshuang Qiao , Siyu An , Kaihua Song , Xiangyue Lin , Hua Chai , Faen Zhang , Jiangliang Guo , Jingbo Huang , Xu Li , Jin Tang , Shiming Yin
IPC: H04N21/466
Abstract: Embodiments of the present disclosure disclose a method and apparatus for recommending a video. A specific implementation of the method includes: finding a recommended video corresponding to a target video from all candidate videos based on similarities of content characteristics of the videos, the target video being a video to be played on a terminal of a user; and sending play information of the recommended video corresponding to the target video to the terminal of the user. The method finds a video similar on video content to the target video that the user desires to view based on the content characteristic of the video, and recommends the video similar on video content to the target video that the user desires to view to the user.
-
公开(公告)号：US11194999B2
公开(公告)日：2021-12-07
申请号：US16102924
申请日：2018-08-14
Inventor： Tianhan Xu , Faen Zhang , Kai Zhou , Qian Wang , Kun Liu , Yuanhao Xiao , Dongze Xu , Jiayuan Sun , Lan Liu
Abstract: An integrated facial recognition method and system. The method includes: receiving a request for acquiring an integrated facial recognition service sent by a user terminal, which includes: an identifier of a user-selected model associated with facial recognition of the user, and an identifier of an operation selected by the user from candidate operations; and executing distributedly an operation selected by the user from the candidate operations on the user-selected model associated with the facial recognition of the user to obtain an operation result, and storing the operation result. The embodiment has realized completing the operations such as training a model or developing a facial recognition application, without the need of buying hardware and establishing a software environment by the user, thereby saving the development cost and improving the convenience of using the facial recognition service.
-
4.发明申请公开(公告)号：US20190213734A1
公开(公告)日：2019-07-11
申请号：US16165518
申请日：2018-10-19
Inventor： Jiabing Leng , Minghao Liu , Yang Liang , Yawei Wen , Faen Zhang , Jiangliang Guo , Jin Tang , Shiming Yin
IPC: G06T7/00
Abstract: The application provides a method and a device for detecting a defect in a steel plate, as well as an apparatus and a server therefor. The method for detecting a defect in a steel plate comprises: receiving image data of the steel plate, and generating a defect detection request according to the image data; monitoring computing loads of a plurality of servers, and sending the image data and the defect detection request to a first server; receiving, from the first server, a detection result obtained by calculating the image data using the detection model; and operating according to the detection result, wherein the detection result comprises a selected one of a pass result and a defect result. With the proposed method, the position and the classification of the at least one defect can be obtained, so that the detection accuracy is improved.
-
公开(公告)号：US11762697B2
公开(公告)日：2023-09-19
申请号：US16248560
申请日：2019-01-15
Inventor： Kun Liu , Kai Zhou , Qian Wang , Yuanhao Xiao , Lan Liu , Dongze Xu , Tianhan Xu , Jiangliang Guo , Jin Tang , Faen Zhang , Shiming Yin
IPC: G06N3/08 , G06F9/50 , G06F18/2413 , G06V10/764 , G06V10/82 , G06F18/21
CPC classification number: G06F9/5027 , G06F9/5011 , G06F18/24143 , G06N3/08 , G06V10/764 , G06V10/82 , G06F18/21
Abstract: The present disclosure discloses a method and apparatus for scheduling a resource for a deep learning framework. The method can comprise: querying statuses of all deep learning job objects from a Kubernetes platform at a predetermined interval; and submitting, in response to finding from the queried deep learning job objects a deep learning job object having a status conforming to a resource request submission status, a resource request to the Kubernetes platform to schedule a physical machine where the Kubernetes platform is located to initiate a deep learning training task. The method can completely automate the allocation and release on the resource of the deep learning training task.
-
Patent Agency Ranking
公开(公告)号：US11276158B2
公开(公告)日：2022-03-15
申请号：US16351291
申请日：2019-03-12
Inventor： Yawei Wen , Jiabing Leng , Minghao Liu , Yulin Xu , Faen Zhang , Jiangliang Guo , Xu Li , Jin Tang
Abstract: A method and an apparatus for inspecting a corrosion defect of a ladle are provided. The method includes: acquiring images from various angles using an image acquisition apparatus inside a to-be-inspected ladle; and inputting the acquired images into a defect inspection system to obtain a label representing a defect category, the defect inspection system including: a deep convolutional neural network that predicts a category of a corrosion defect of the ladle included in the images based on the input images. This method has the advantages of high safety, high accuracy and high real-time performance in inspecting the ladle status.
-
公开(公告)号：US10950328B2
公开(公告)日：2021-03-16
申请号：US15495307
申请日：2017-04-24
Inventor： Ziye Shi , Shan He , Dongze Xu , Faen Zhang , Lizhi Wu
Abstract: A method, apparatus and system for detecting structural variations is provided. A management apparatus divides a test sequence according to loci of chromosomes to obtain at least two portions of detection tasks, sends respective detection tasks to respective detection apparatuses and activates the respective detection tasks; detects detection task completion situations of detection apparatuses and determines whether the number of uncompleted tasks is reduced to a preset proportion threshold of a total number of tasks; when the number is reduced to a preset proportion threshold of the total number of tasks, the management apparatus sends, to detection apparatuses that have not yet completed detection tasks, an instruction message to kill uncompleted detection tasks; the management apparatus further divides the uncompleted detection tasks into at least two portions, sends respective detection tasks to respective detection apparatuses, and activates said respective detection apparatuses to continue to perform detection of structural variations.
-
公开(公告)号：US20190228303A1
公开(公告)日：2019-07-25
申请号：US16248560
申请日：2019-01-15
Inventor： Kun LIU , Kai Zhou , Qian Wang , Yuanhao Xiao , Lan Liu , Dongze Xu , Tianhan Xu , Jiangliang Guo , Jin Tang , Faen Zhang , Shiming Yin
Abstract: The present disclosure discloses a method and apparatus for scheduling a resource for a deep learning framework. The method can comprise: querying statuses of all deep learning job objects from a Kubernetes platform at a predetermined interval; and submitting, in response to finding from the queried deep learning job objects a deep learning job object having a status conforming to a resource request submission status, a resource request to the Kubernetes platform to schedule a physical machine where the Kubernetes platform is located to initiate a deep learning training task. The method can completely automate the allocation and release on the resource of the deep learning training task.
-
公开(公告)号：US20180082015A1
公开(公告)日：2018-03-22
申请号：US15495307
申请日：2017-04-24
Inventor： Ziye SHI , Shan He , Dongze Xu , Faen Zhang , Lizhi Wu
CPC classification number: G16B50/00 , G01N35/00871 , G01N35/0092 , G01N2035/0094
Abstract: The present disclosure provides a method, apparatus and system for detecting structural variations. The method comprises: a management apparatus divides a test sequence according to loci of chromosomes to obtain at least two portions of detection tasks; the management apparatus sends respective detection tasks to respective detection apparatuses and activates the respective detection tasks; the management apparatus detects detection task completion situations of detection apparatuses and determines whether the number of uncompleted tasks is reduced to a preset proportion threshold of a total number of tasks; when the number of uncompleted tasks is reduced to a preset proportion threshold of the total number of tasks, the management apparatus sends, to detection apparatuses that have not yet completed detection tasks, an instruction message to kill uncompleted detection tasks; the management apparatus further divides the uncompleted detection tasks into at least two portions, sends respective detection tasks to respective detection apparatuses, and activates said respective detection apparatuses to continue to perform detection of structural variations. The technical solutions of the present disclosure are employed to sufficiently use the computer resources, quicken the detection process of structural variations of the whole test sequence, and shorten the detection duration of the structural variations of the whole test sequence.
-
10.发明授权公开(公告)号：US11315034B2
公开(公告)日：2022-04-26
申请号：US16118197
申请日：2018-08-30
Inventor： Kai Zhou , Qian Wang , Faen Zhang , Kun Liu , Yuanhao Xiao , Dongze Xu , Tianhan Xu , Jiayuan Sun , Lan Liu
Abstract: A system comprises: a data warehouse, a storage device and a cluster including a plurality of computing nodes; the data warehouse is configured to store task data obtained from the user; at least one computing node in the cluster includes a resource scheduling component, and is configured to perform resource scheduling for the task and determine a computing node executing the task; the computing node executing the task comprises a model training component and/or a prediction component; the model training component is configured to, according to task data, invoke a corresponding type of learning model from the storage device; use sample data and training target included in the task data to train the learning model, to obtain the prediction model corresponding to the task and store the prediction model in the storage device; the prediction component is configured to obtain a prediction result output by the prediction model.
-
-
-
-
-
-
-
-
-
Search Results
14
records
(took 0.034 seconds)
