Suzhou Metabrain Intelligent Technology Co., Ltd.

Potent Sports & Tech Co., Ltd.

Inspur Suzhou Intelligent Technology Co., Ltd

Jiangsu Xcmg Construction Machinery Research Institute Ltd.

Li Wang

Baoyu Fan

Yaqian Zhao

Rengang Li

Zhenhua Guo

Yanbo Geng

Yong Zhang

Nan Wu

Xiangyi Deng

Chunlei Liu

Disclosed is an intelligent learning and adjustment system for a tennis training robot, including an image recognition system, an algorithm model, a back-end processing platform, and an optimization model. Preprocessing of incoming ball data is performed, various necessary data, such as speeds and directions of flying tennis balls, spinning and placements, are collected, various data sets are processed by using various machine learning algorithms, effective predictions and decisions are generated to facilitate the prediction of the placement and difficulty level of the incoming ball, so that a capability and level of a sparring athlete can be evaluated, the tennis training robot accordingly makes prediction and recognition, and carries out interactive feedback actions in a timely manner. The entire training process involves continuously updating of weights and bias values to make the predictions increasingly accurate, and the tennis training robot can provide an interactive intelligent training method.

Intelligent learning and adjustment system for tennis training robot

A natural language processing method and apparatus, a device, and a readable storage medium, where the method includes: obtaining a target sentence to be processed, and determining each entity in the target sentence (S); for each entity in the target sentence, in response to the entity being present in a preset entity set, determining extended information for the entity, and adding the determined extended information after a location of the entity in the target sentence, to obtain an updated target sentence (S); and inputting the updated target sentence to a bidirectional encoder representations from transformer (BERT) model, such that the BERT model performs a natural language processing task, where in a process in which the BERT model performs the natural language processing task, an attention score between extended information of any entity in the target sentence and another entity in the target sentence is adjusted to zero (S).

Natural language processing method and apparatus, device, and readable storage medium using a three dimensional tensor to determine a relation between entities to aid in a question-answering task

Embodiments of the present application disclose a natural language processing method and apparatus, a device, and a readable storage medium. The method includes: obtaining a target sentence to be processed, and determining each first entity in the target sentence; for each first entity, in response to the first entity being present in a preset entity set, determining, in the preset entity set, a second entity in maximum correlation with the first entity, generating extended information based on the determined second entity, and adding the extended information after a location of the first entity in the target sentence, to obtain an updated target sentence, where the second entity is any entity in the preset entity set other than the first entity; and inputting the updated target sentence to a bidirectional encoder representations from transformer (BERT) model, such that the BERT model performs a natural language processing task.

Natural language processing method and apparatus, device, and readable storage medium

Disclosed in the present disclosure are an image-text mutual retrieval model training method and apparatus, an image-text mutual retrieval method, and a device, applied to the technical field of retrieval. The image-text mutual retrieval model training method includes: acquiring training data pairs; inputting the training data pair in an initial model, and extracting text coding features of text training data and image coding features of image training data by using a text coding module and an image coding module in the initial model, respectively; calculating a training loss based on the text coding features and the image coding features, and performing parameter adjustment on the initial model based on the training loss; and in response to the training loss meeting a convergence condition, determining the initial model after the parameter adjustment as an image-text mutual retrieval model.

Method and apparatus for training an image-text mutual retrieval model, image-text mutual retrieval method, and device

Disclosed is an image segmentation method, including: obtaining an original image set; performing feature extraction on the original image set by using a backbone network to obtain a feature map set; performing channel extraction fusion processing on the feature map set by using a channel extraction fusion model to obtain an enhanced feature map set; and segmenting the enhanced feature map set by using a preset convolutional neural network to obtain an image segmentation result. In addition, the present application also provides an image segmentation system and device, and a readable storage medium, which have the beneficial effects above.

Image segmentation method, system, and device, and readable storage medium

The present application discloses a person re-identification method, system and device, and a computer-readable storage medium. The method includes: obtaining a first type of person image without a label; making label information for the first type of person image; training a target person re-identification network on the basis of the first type of person image and the label information to obtain a first trained target person re-identification network; extracting a region of interest in the first type of person image; and training, on the basis of the first type of person image and the region of interest, the first trained target person re-identification network to obtain a second trained target person re-identification network, and performing person re-identification on the basis of the target person re-identification network.

Person re-identification method, system and device, and computer-readable storage medium

Provided in the present application are a disk processing method and system, and an electronic device. The method comprises: when disk alarm information is detected, marking a corresponding alarm disk as a faulty disk; detecting the state of a disk group corresponding to the faulty disk; if the state of the disk group is degraded, marking the faulty disk as an isolation disk, and generating alarm information; if the state of the disk group is healthy, determining whether there is a redundant disk group; if there is no redundant disk group, operating the faulty disk according to a first preset rule, and generating alarm information; and if there is a redundant disk group, detecting the state of the redundant disk group, if the state of the redundant disk group is healthy, marking the faulty disk as the isolation disk, and generating alarm information, otherwise, operating the faulty disk according to a second preset rule, and generating alarm information.

Pedestrian re-identification method, system and device, and computer-readable storage medium

Disclosed is an ice hockey ball-controlling skill training device, which comprises a plurality of cross members hinged end to end, and the connecting ends of adjacent two cross members are provided with fixing components for connecting and fixing; the training device also compromises a ball, LED lighting components, and induction components, the induction component compromises a plurality of Hall elements and electromagnetic induction elements, a plurality of Hall elements are respectively arranged on a plurality of cross members, the electromagnetic induction elements are arranged in the ball; when the ball passes under the cross member, the electromagnetic induction elements can triggers induction with Hall elements. During the training process, when the ball passes under the cross member, the electromagnetic induction element can trigger induction with the Hall element. Compared with the ball control device in the prior art, the device has more accurate induction.

Ball control skill training device for ice hockey

A rollover alarming system, a rollover risk prediction method, and a rollover alarming method. An axle housing strain measurement unit measures strain values on both sides of an axle housing of a vehicle body. A roll angle measurement unit measures a roll angle of the vehicle body. A collection control unit is configured to collect the strain values on both sides of the axle housing of the vehicle body and the roll angle of the vehicle body, calculate a strain difference between the strain values according to the strain values on both sides of the axle housing of the vehicle body, and output a corresponding alarm control signal according to the strain difference between both sides of the axle housing of the vehicle body and the roll angle of the vehicle body. An alarm unit is configured to output a corresponding alarm signal according to the received alarm control signal.

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Jiangsu, China

Li Wang