Landslide identification method and system based on attention mechanism and multi-modal representation learning

A recognition method and attention technology, which are applied in the field of image processing, can solve the problems of consuming computer memory and computing resources, and cannot be applied, so as to avoid gradient disappearance or gradient explosion, improve convergence speed and model accuracy, and expand training data.

Pending Publication Date: 2022-03-11
XIDIAN UNIV
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Problems solved by technology

The disadvantage of this method is that using high-precision images and elevation data to generate a 3D model will greatly consume the memory and computing resources of the computer, which will make this technology unable to be used in embedded mobile platforms with limited memory and computing resources. apply

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  • Landslide identification method and system based on attention mechanism and multi-modal representation learning
  • Landslide identification method and system based on attention mechanism and multi-modal representation learning
  • Landslide identification method and system based on attention mechanism and multi-modal representation learning

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[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0060] In the description of the present invention, it should be understood that the terms "comprising" and "comprising" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or more other features, Presence or addition of wholes, steps, operations, elements, components and / or collections thereof.

[0061] It should also be understood that the terminology used in the descriptio...

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Abstract

The invention discloses a landslide identification method and system based on an attention mechanism and multi-modal representation learning. The method comprises the following steps: dividing a positive sample containing a landslide and a negative sample containing a non-landslide into a training set, a verification set and a test set; carrying out data enhancement on the training set, adjusting the image sizes of the verification set, the test set and the training set after data enhancement, and normalizing the pixel value of each channel of the image; constructing a multi-channel convolutional neural network based on an attention mechanism and multi-modal representation learning; using a cross entropy loss function to train the multi-channel convolutional neural network based on the attention mechanism and the multi-modal representation learning; using the normalized training set to train the trained attention mechanism and the multi-modal representation learning multi-path convolutional neural network, using the normalized verification set to verify, and storing the network model with the best performance on the verification set; and testing on the stored network model by using the normalized test set to obtain a landslide identification result, thereby reducing the consumption of computing resources.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a landslide recognition method and system based on attention mechanism and multimodal representation learning. Background technique [0002] Landslide identification is an image analysis technology that determines the area, scale and distribution of landslides by analyzing the shape and characteristics of the landslide area. Landslide identification is the basis of landslide hazard evaluation, the premise of rational allocation of monitoring resources and effective early warning, and occupies a key position in the study of landslide hazards. [0003] However, when performing landslide identification, most landslides have obvious roughness and prominent texture features. The landslide body is often mixed with some vegetation, which is a mixture of soil and vegetation, making its performance on optical images more complicated. At the same time, due to the obvi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/17G06V10/774G06K9/62G06N3/04
CPCG06N3/045G06F18/214
Inventor 王蓉芳魏浩江李卫斌刘若辰刘波尚荣华郝红侠
Owner XIDIAN UNIV
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