Data sampling and model training method and device, equipment and storage medium

A data sampling and sampling point technology, which is applied in character and pattern recognition, instruments, computing, etc., can solve the problem of poor data sampling distribution balance, and achieve the effect of improving distribution balance and expanding coverage.

Pending Publication Date: 2022-07-01
GUANGZHOU WERIDE TECH LTD CO
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Problems solved by technology

[0006] The present application aims to solve at least one of the above-mentioned technical defects. In view of this, the present application provides a data sampling and model training method, device, equipment and storage medium, which are used to solve the problem of data sampling distribution balance in the prior art. Poor technical flaws

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  • Data sampling and model training method and device, equipment and storage medium
  • Data sampling and model training method and device, equipment and storage medium
  • Data sampling and model training method and device, equipment and storage medium

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Embodiment Construction

[0067] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0068] Combine below figure 1 , the process of the data sampling method given in the embodiment of the present application is introduced, such as figure 1 As shown, the process can include the following steps:

[0069] Step S101: Preliminarily classify all the sampling points of the geographic location to be sampled to obtain a plurality of initial clusters.

[0070] Specifically, after determining the geographic location of the data to be sampled,...

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Abstract

The invention provides a data sampling and model training method and device, equipment and a storage medium, and the method comprises the steps: carrying out the splitting and refining of a clustering result of a to-be-sampled geographic position into a plurality of sub-clusters, determining the total amount of sampling data of each sub-cluster according to the area of a region defined by each sampling point of each sub-cluster, and carrying out the calculation of the total amount of sampling data of each sub-cluster. The method comprises the following steps of: firstly, performing multiple times of random sampling on each sub-cluster, calculating the distribution balance of each time of random sampling of each sub-cluster, and determining a sampling result with the most balanced distribution as a final sampling result of each sub-cluster. The distribution balance of the sampling data of each sub-cluster is effectively improved, and the overall distribution balance of the total amount of the sampling data is improved. In addition, training data can be collected by using the data sampling method so as to be used for training an unmanned vehicle control model capable of processing one or more of perception, prediction and decision-making tasks of the unmanned vehicle.

Description

technical field [0001] The present application relates to the technical field of data sampling, and in particular, to a data sampling and model training method, apparatus, device, and storage medium. Background technique [0002] With the development of science and technology, the technology of automatic driving has also developed rapidly. In the technical field of automatic driving, many automatic driving technology algorithms are involved, and the realization of these automatic driving technology algorithms sometimes requires the use of some deep neural network models. In order to better implement some autonomous driving technology algorithms involved in autonomous driving technology, it is necessary to collect a large number of data samples from a large range of geographic locations as training data to train some neural network models involved in autonomous driving technology algorithms. [0003] For example, when it is necessary to train a recognition model that can judg...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23213G06F18/214
Inventor 孙子文陈飞韩旭
Owner GUANGZHOU WERIDE TECH LTD CO
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