A semi-automatic image annotation method based on online learning

An image annotation, semi-automatic technology, applied in the field of data engineering, to achieve the effect of improving efficiency

Active Publication Date: 2022-03-04
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is: aiming at the time-consuming problem of manually preparing training data in the field of target detection, by learning while labeling, extracting and utilizing the supervision information existing in the manual labeling process to improve the automation of image labeling, Improve the efficiency of data set preparation

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  • A semi-automatic image annotation method based on online learning
  • A semi-automatic image annotation method based on online learning
  • A semi-automatic image annotation method based on online learning

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Embodiment Construction

[0057] In order to clarify the purpose, content and advantages of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings. The invention relates to a semi-automatic image labeling method based on online learning, comprising the following steps:

[0058] (1) Determine the number of target categories that exist in the image set to be labeled, and initialize a multi-class logistic regression classifier;

[0059](2) Input the image to be labeled and execute the manual labeling mode: complete the labeling of all the targets in the image by manually selecting the target position and manually annotating the target category, and train the classifier online through these labeled data;

[0060] (3) Test classifier performance, and decide whether to switch from manual labeling mode to semi-automatic labeling mode based on classifier performance;

[0061] (4) Input the image to be labeled, and execute the semi-a...

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Abstract

The invention belongs to the field of data engineering, and specifically discloses a semi-automatic image labeling method based on online learning, which is used for preparing training data for a learning-based image target detection method. Aiming at the time-consuming problem of manually preparing training data in the field of target detection, this method extracts and utilizes the supervision information existing in the manual labeling process by learning while labeling, which improves the automation of image labeling and improves the efficiency of data set preparation. efficiency.

Description

technical field [0001] The invention relates to a semi-automatic image labeling method based on online learning, which belongs to the field of data engineering and is used for preparing training data for a learning-based image target detection method. Background technique [0002] In recent years, deep learning technology represented by convolutional neural network has been widely used in the field of image object detection due to its powerful feature learning ability. The preparation of training data is a necessary condition for feature learning. Data annotation in the detection domain includes two steps: frame selection and annotation. Frame selection refers to selecting the target and marking the outer rectangular frame of the target; annotation refers to providing the category information of the target. [0003] At present, the preparation of training data usually relies on human labeling, and some interactive auxiliary labeling tools can reduce the burden of labelers ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/774G06V10/764G06V10/50G06K9/62
CPCG06V10/50G06F18/214G06F18/24
Inventor 傅瑞罡高颖慧董小虎李飚朱永锋
Owner NAT UNIV OF DEFENSE TECH
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