Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

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
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • 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

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[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...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com