Cargando…

Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation

GIS technology can provide reasonable and sustainable data support for landscape planning and ecological development and make wetland landscape planning consider the spatial layout of landscape and the optimal allocation of resources more. The key technologies of cross media intelligence mainly focu...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Xiaoqing, Wang, Juanfen, Rui, Xiao, Zhang, Jizhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477577/
https://www.ncbi.nlm.nih.gov/pubmed/36120670
http://dx.doi.org/10.1155/2022/8339895
_version_ 1784790391694819328
author Liu, Xiaoqing
Wang, Juanfen
Rui, Xiao
Zhang, Jizhi
author_facet Liu, Xiaoqing
Wang, Juanfen
Rui, Xiao
Zhang, Jizhi
author_sort Liu, Xiaoqing
collection PubMed
description GIS technology can provide reasonable and sustainable data support for landscape planning and ecological development and make wetland landscape planning consider the spatial layout of landscape and the optimal allocation of resources more. The key technologies of cross media intelligence mainly focus on intelligent information retrieval, analysis and reasoning, knowledge map construction, and intelligent storage. Convolutional neural network (CNN), as one of the representative algorithms of deep learning, plays an important role in retrieving landscape data and extracting image and text features across media. Further retrieval of media data, in-depth text processing, and image feature data extraction are realized by using deep learning technology, and comprehensive in-depth analysis is carried out by combining landscape plane images, three-dimensional images, and vector information in GIS technology. Provide quantitative information for the evaluation system of human landscape, economy, history, and region, so as to formulate a scientific and reasonable performance evaluation system.
format Online
Article
Text
id pubmed-9477577
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-94775772022-09-16 Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation Liu, Xiaoqing Wang, Juanfen Rui, Xiao Zhang, Jizhi Comput Intell Neurosci Research Article GIS technology can provide reasonable and sustainable data support for landscape planning and ecological development and make wetland landscape planning consider the spatial layout of landscape and the optimal allocation of resources more. The key technologies of cross media intelligence mainly focus on intelligent information retrieval, analysis and reasoning, knowledge map construction, and intelligent storage. Convolutional neural network (CNN), as one of the representative algorithms of deep learning, plays an important role in retrieving landscape data and extracting image and text features across media. Further retrieval of media data, in-depth text processing, and image feature data extraction are realized by using deep learning technology, and comprehensive in-depth analysis is carried out by combining landscape plane images, three-dimensional images, and vector information in GIS technology. Provide quantitative information for the evaluation system of human landscape, economy, history, and region, so as to formulate a scientific and reasonable performance evaluation system. Hindawi 2022-09-08 /pmc/articles/PMC9477577/ /pubmed/36120670 http://dx.doi.org/10.1155/2022/8339895 Text en Copyright © 2022 Xiaoqing Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liu, Xiaoqing
Wang, Juanfen
Rui, Xiao
Zhang, Jizhi
Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation
title Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation
title_full Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation
title_fullStr Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation
title_full_unstemmed Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation
title_short Application of GIS Technology-Supported Cross Media Fusion Method Based on Deep Learning in Landscape Performance Evaluation
title_sort application of gis technology-supported cross media fusion method based on deep learning in landscape performance evaluation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477577/
https://www.ncbi.nlm.nih.gov/pubmed/36120670
http://dx.doi.org/10.1155/2022/8339895
work_keys_str_mv AT liuxiaoqing applicationofgistechnologysupportedcrossmediafusionmethodbasedondeeplearninginlandscapeperformanceevaluation
AT wangjuanfen applicationofgistechnologysupportedcrossmediafusionmethodbasedondeeplearninginlandscapeperformanceevaluation
AT ruixiao applicationofgistechnologysupportedcrossmediafusionmethodbasedondeeplearninginlandscapeperformanceevaluation
AT zhangjizhi applicationofgistechnologysupportedcrossmediafusionmethodbasedondeeplearninginlandscapeperformanceevaluation