Robot multi-degree-of-freedom clamper

    公开(公告)号:US11458638B2

    公开(公告)日:2022-10-04

    申请号:US16957720

    申请日:2018-12-20

    Abstract: A robot multi-degree-of-freedom clamper has a short stroke biaxial cylinder installed on the clamping jaw supporting frame and an output end connected with a pneumatic clamping jaw A. In addition, a clamping jaw finger A is connected with an output end of the pneumatic clamping jaw A. A long stroke biaxial cylinder is connected with a pneumatic clamping jaw B. A clamping jaw finger B is connected with the output end of the pneumatic clamping jaw B. A pneumatic clamping jaw C is positioned between the pneumatic clamping jaw A and the pneumatic clamping jaw B. A clamping jaw finger C is connected with the output end of the pneumatic clamping jaw C. The clamping jaw finger A and the pneumatic clamping jaw A are driven by the short stroke biaxial cylinder to move back and forth on the clamping jaw supporting frame.

    OPTIMIZATION DECISION-MAKING METHOD OF INDUSTRIAL PROCESS FUSING DOMAIN KNOWLEDGE AND MULTI-SOURCE DATA

    公开(公告)号:US20220260981A1

    公开(公告)日:2022-08-18

    申请号:US17560878

    申请日:2021-12-23

    Abstract: Disclosed is an optimization decision-making method of an industrial process fusing domain knowledge and multi-source data. The method comprises the steps of: acquiring the domain knowledge of the industrial process by using probability soft logic, and building an domain rule knowledge base of the industrial process; fusing multi-source data semantics and multi-source data features to form a new semantic knowledge representation of the industrial process, and constructing a semantic knowledge base of the industrial process; under a posteriori regularization framework, utilizing the domain rule knowledge base of the industrial process and the semantic knowledge base of the industrial process to obtain an optimization decision-making model embedded with the domain rule knowledge and obtain a posteriori distribution model; and migrating knowledge in the optimization decision-making model embedded with the domain rule knowledge into the posteriori distribution model through the knowledge distillation technology.

    Method for generating transcranial magnetic stimulation (TMS) coil pose atlas based on electromagnetic simulating calculation

    公开(公告)号:US11369282B1

    公开(公告)日:2022-06-28

    申请号:US17539150

    申请日:2021-11-30

    Abstract: A method for generating a transcranial magnetic stimulation (TMS) coil pose atlas based on electromagnetic simulating calculation includes: constructing coil array positions and orientations of a scalp in a standard Montreal Neurological Institute (MNI) space and matching the coil array positions and orientations of the scalp to a brain space of an individual to obtain coil array positions and orientations of the brain space of the individual; using a finite element calculation method to simulate the coil array positions of the brain space of the individual to obtain induced electric field distributions of brain tissue in different coil orientations; obtaining optimal regulation effects based on the induced electric field distributions of the brain tissue; and obtaining a coil position and orientation corresponding to each optimal regulation effect as an optimal coil pose of each divided brain area of the individual, and constructing a TMS coil pose atlas of the individual.

    Automatic depression detection method and device, and equipment

    公开(公告)号:US11266338B1

    公开(公告)日:2022-03-08

    申请号:US17389381

    申请日:2021-07-30

    Abstract: An automatic depression detection method includes the following steps of: inputting audio and video files, wherein the audio and video files contain original data in both audio and video modes; conducting segmentation and feature extraction on the audio and video files to obtain a plurality of audio segment horizontal features and video segment horizontal features; combining segment horizontal features into an audio horizontal feature and a video horizontal feature respectively by utilizing a feature evolution pooling objective function; and conducting attentional computation on the segment horizontal features to obtain a video attention audio feature and an audio attention video feature, splicing the audio horizontal feature, the video horizontal feature, the video attention audio feature and the audio attention video feature to form a multimodal spatio-temporal representation, and inputting the multimodal spatio-temporal representation into support vector regression to predict the depression level of individuals in the input audio and video files.

    Multi-modal lie detection method and apparatus, and device

    公开(公告)号:US11244119B1

    公开(公告)日:2022-02-08

    申请号:US17389383

    申请日:2021-07-30

    Abstract: A multi-modal lie detection method and apparatus, and a device to improve an accuracy of an automatic lie detection are provided. The multi-modal lie detection method includes inputting original data of three modalities, namely a to-be-detected audio, a to-be-detected video and a to-be-detected text; performing a feature extraction on input contents to obtain deep features of the three modalities; explicitly depicting first-order, second-order and third-order interactive relationships of the deep features of the three modalities to obtain an integrated multi-modal feature of each word; performing a context modeling on the integrated multi-modal feature of the each word to obtain a final feature of the each word; and pooling the final feature of the each word to obtain global features, and then obtaining a lie classification result by a fully-connected layer.

    Expression recognition method under natural scene

    公开(公告)号:US11216652B1

    公开(公告)日:2022-01-04

    申请号:US17470135

    申请日:2021-09-09

    Abstract: An expression recognition method under a natural scene comprises: converting an input video into a video frame sequence in terms of a specified frame rate, and performing facial expression labeling on the video frame sequence to obtain a video frame labeled sequence; removing natural light impact, non-face areas, and head posture impact elimination on facial expression from the video frame labeled sequence to obtain an expression video frame sequence; augmenting the expression video frame sequence to obtain a video preprocessed frame sequence; from the video preprocessed frame sequence, extracting HOG features that characterize facial appearance and shape features, extracting second-order features that describe a face creasing degree, and extracting facial pixel-level deep neural network features by using a deep neural network; then, performing vector fusion on these three obtain facial feature fusion vectors for training; and inputting the facial feature fusion vectors into a support vector machine for expression classification.

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