Neural network migration learning method based on virtual image dataset

An image data set and neural network technology, applied in the field of machine deep learning, can solve problems such as long multi-model training time, difficulty in collecting and training training data sets, and small training database

Inactive Publication Date: 2017-12-08
XIDIAN UNIV
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Problems solved by technology

[0003] To sum up, the problems existing in the existing technology are: the existing transfer learning technology cannot solve the difficulty of collecting and training training data se

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  • Neural network migration learning method based on virtual image dataset
  • Neural network migration learning method based on virtual image dataset
  • Neural network migration learning method based on virtual image dataset

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Embodiment Construction

[0031] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0032] The application principle of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0033] like figure 1 As shown, the neural network migration learning method based on the virtual image data set provided by the embodiment of the present invention includes the following steps:

[0034] S101: By preprocessing the virtual image, including image size adjustment, image flipping, image color adjustment, image clipping and translation, etc.; by preprocessing the image, the model can be prevented from being affected by irrelevant factors; (such as lighting factors , occlus...

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Abstract

The invention belongs to the field of machine learning technology and discloses a neural network migration learning method based on a virtual image dataset. The method comprises the steps that virtual image data is acquired through graphic simulation software, classified marking is performed on a virtual dataset, and an image dataset is obtained; a neural network is utilized to train a target recognition model through preprocessing of the virtual dataset, and a parameter model trained through the virtual dataset is saved; and migration learning is performed, and a new target dataset is utilized to train the saved pre-training model again. According to the method, a needed scene or target is collected through a virtual engine to construct a dataset based on the virtual image dataset, the pre-training model is obtained through training of the virtual dataset, and the migration learning method is utilized to achieve the practical application effect on a small quantity of datasets.

Description

technical field [0001] The invention belongs to the technical field of machine deep learning, and in particular relates to a neural network migration learning method based on a virtual image data set. Background technique [0002] With the development of machine learning, recognition technology in various complex scenes has become more and more important, but it is difficult to collect target data in some extreme environments and data sets from special perspectives (such as the drone's overlooking angle). Some public datasets cannot meet the needs of pattern recognition training datasets in specific scenarios. However, training a complex neural network requires a large amount of labeled data, which not only consumes a lot of manpower and material resources, but even with a large amount of training data, it takes days or even weeks to train a complex convolutional neural network. The problem of difficulty in collecting data sets in the environment and special perspectives, a...

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Application Information

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IPC IPC(8): G06N99/00G06N3/08
CPCG06N3/08G06N20/00
Inventor 刘志彬裴庆祺罗毅段厚华付家瑄王顺其文浩斌
Owner XIDIAN UNIV
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