{
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  "description": "A pedestrian adaptive zero-velocity update point selection method based on a neural network, including the following steps: S collecting inertial navigation data of different pedestrians in different motion modes; S preprocessing the inertial navigation data collected in the step S labeling the…",
  "path": "/patents/1286040",
  "publishedAt": "2021-03-18T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G01C21/18",
    "University of Electronic Science and Technology of China"
  ],
  "textContent": "A pedestrian adaptive zero-velocity update point selection method based on a neural network, including the following steps: S collecting inertial navigation data of different pedestrians in different motion modes; S preprocessing the inertial navigation data collected in the step S labeling the preprocessed data, and obtaining a training data set, a validation data set, and a test data set according to the preprocessed data and a label corresponding to the preprocessed data; S inputting the training data set to a convolutional neural network for training, obtaining a pedestrian adaptive zero-velocity update point selection model based on the convolutional neural network, and using the validation data set to validate the pedestrian adaptive zero-velocity update point selection model; and S inputting the test data set into the pedestrian adaptive zero-velocity update point selection model based on the convolutional neural network, and obtaining a selection result of pedestrian zero-velocity update points.",
  "title": "PEDESTRIAN ADAPTIVE ZERO-VELOCITY UPDATE POINT SELECTION METHOD BASED ON A NEURAL NETWORK"
}