Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Deep learning and GIS integration for plant disease diagnosis and management

Saved in:
Bibliographic Details
Published in:Discover AI
Format: Online Article RSS Article
Published: 2026
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864030192737976320
collection WordPress RSS
FRELIP Feed Integration
container_title Discover AI
description
discipline_display Education
discipline_facet Education
format Online Article
RSS Article
genre Journal Article
id rss_article:39740
institution FRELIP
journal_source_facet Discover AI
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Deep learning and GIS integration for plant disease diagnosis and management
— — — — — Access Artificial Intelligence and Machine Learning
Higher Education
Education
sub_discipline_display Higher Education
sub_discipline_facet Higher Education
subject_display — — — — — Access Artificial Intelligence and Machine Learning
Higher Education
Education
— — — — — Access Artificial Intelligence and Machine Learning
Higher Education
Education
subject_facet — — — — — Access Artificial Intelligence and Machine Learning
Higher Education
Education
title Deep learning and GIS integration for plant disease diagnosis and management
title_auth Deep learning and GIS integration for plant disease diagnosis and management
title_full Deep learning and GIS integration for plant disease diagnosis and management
title_fullStr Deep learning and GIS integration for plant disease diagnosis and management
title_full_unstemmed Deep learning and GIS integration for plant disease diagnosis and management
title_short Deep learning and GIS integration for plant disease diagnosis and management
title_sort deep learning and gis integration for plant disease diagnosis and management
topic — — — — — Access Artificial Intelligence and Machine Learning
Higher Education
Education
url https://link.springer.com/article/10.1007/s44163-025-00811-x