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Advanced image segmentation for precision agriculture using CNN-GAT fusion and fuzzy C-means clustering
In recent years, the use of convolutional neural networks (CNNs) and graph convolutional
networks (GCNs) has significantly advanced hyperspectral image classification (HSIC) …
networks (GCNs) has significantly advanced hyperspectral image classification (HSIC) …
Advanced plant disease segmentation in precision agriculture using optimal dimensionality reduction with fuzzy c-means clustering and deep learning
Analysis of hyperspectral imagery is a critical aspect of remote sensing in precision
agriculture, for which effective dimensionality reduction (DR) strategies for the inherent …
agriculture, for which effective dimensionality reduction (DR) strategies for the inherent …
Material flows and embodied carbon emissions of aluminum used in China's photovoltaic industry from 2000 to 2020
China is a global leader in the photovoltaic industry, yet research into the aluminum
resource consumption and associated carbon emissions from photovoltaic production …
resource consumption and associated carbon emissions from photovoltaic production …
Mitigating development barriers and addressing disparities in border cities of Iran: a comprehensive analysis of border provinces and influential factors
This study addresses the persistent challenge of development disparities in Iran's border
regions. Despite the nation's commitment to reducing the development gap between its …
regions. Despite the nation's commitment to reducing the development gap between its …
Sunflower-YOLO: Detection of sunflower capitula in UAV remote sensing images
R **g, Q Niu, Y Tian, H Zhang, Q Zhao, Z Li… - European Journal of …, 2024 - Elsevier
Accurate identification and monitoring of sunflower capitula are crucial for field phenotypic
analysis, cultivation management, phenological monitoring, and yield prediction. Manual …
analysis, cultivation management, phenological monitoring, and yield prediction. Manual …
Exploring multi-pollution variability in the urban environment: geospatial AI-driven modeling of air and noise
This study addresses the critical need for comprehensive multi-pollution modeling in urban
environments by employing Geospatial Artificial Intelligence (GeoAI) techniques …
environments by employing Geospatial Artificial Intelligence (GeoAI) techniques …
Significant impact of the covid-19 pandemic on methane emissions evaluated by comprehensive statistical analysis of satellite data
The COVID-19 pandemic has significantly influenced various aspects of society, including
environmental factors such as methane emissions. This study investigates the changes in …
environmental factors such as methane emissions. This study investigates the changes in …
Multi-objective optimisation and energy-saving design of pressure-swing extractive distillation for separating ethanol/acetonitrile/water azeotropic system
Extractive distillation has been widely used in the separation and purification of azeotropes
generated in downstream chemical processes. However, the limitations of extractive …
generated in downstream chemical processes. However, the limitations of extractive …
HM–GDM: Hybrid Measures and Graph-Dependent Modeling for Environmental Sound Classification
One of the upcoming areas of research is the automated environmental sound classification,
as its application is highly utilized in criminal investigations scenarios, surveillance systems …
as its application is highly utilized in criminal investigations scenarios, surveillance systems …
Application of remote sensing image processing based on artificial intelligence in landscape pattern analysis
Q Zhang - Environmental Earth Sciences, 2024 - Springer
The spatial arrangement of various land cover types within a landscape is referred to as the
Landscape Pattern (LSP). An essential component of landscape ecology, LSP examination …
Landscape Pattern (LSP). An essential component of landscape ecology, LSP examination …