Data fusion in agriculture: Resolving ambiguities and closing data gaps
JGA Barbedo - Sensors, 2022 - mdpi.com
Acquiring useful data from agricultural areas has always been somewhat of a challenge, as
these are often expansive, remote, and vulnerable to weather events. Despite these …
these are often expansive, remote, and vulnerable to weather events. Despite these …
Deep separable convolutional network for remaining useful life prediction of machinery
Deep learning is gaining attention in data-driven remaining useful life (RUL) prediction of
machinery because of its powerful representation learning ability. With the help of deep …
machinery because of its powerful representation learning ability. With the help of deep …
A systematic review of UAV applications for mapping neglected and underutilised crop species' spatial distribution and health
Timely, accurate spatial information on the health of neglected and underutilised crop
species (NUS) is critical for optimising their production and food and nutrition in developing …
species (NUS) is critical for optimising their production and food and nutrition in developing …
Temporal convolutional network with soft thresholding and attention mechanism for machinery prognostics
Remaining useful life (RUL) prediction is a challenging task for prognostics and health
management (PHM). Due to the complexity physics involved for precisely modeling the …
management (PHM). Due to the complexity physics involved for precisely modeling the …
Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions
Geospatial artificial intelligence (GeoAI) has emerged as a subfield of GIScience that uses
artificial intelligence approaches and machine learning techniques for geographic …
artificial intelligence approaches and machine learning techniques for geographic …
Forecasting foreign exchange volatility using deep learning autoencoder‐LSTM techniques
Since the breakdown of the Bretton Woods system in the early 1970s, the foreign exchange
(FX) market has become an important focus of both academic and practical research. There …
(FX) market has become an important focus of both academic and practical research. There …
[HTML][HTML] Relationship between landscape and river ecosystem services
Landscape dynamics are a consequence of population growth, which can degrade river
ecosystem services. Since various countries approved the millennium ecosystem …
ecosystem services. Since various countries approved the millennium ecosystem …
[HTML][HTML] WorldCereal: a dynamic open-source system for global-scale, seasonal, and reproducible crop and irrigation mapping
K Van Tricht, J Degerickx, S Gilliams… - Earth System …, 2023 - essd.copernicus.org
The challenge of global food security in the face of population growth, conflict, and climate
change requires a comprehensive understanding of cropped areas, irrigation practices, and …
change requires a comprehensive understanding of cropped areas, irrigation practices, and …
Identifying the most influential parameters in predicting lighting energy consumption in office buildings using data-driven method
S Norouziasl, A Jafari - Journal of Building Engineering, 2023 - Elsevier
Predicting building energy consumption is a necessary step in energy management, energy
saving and optimization. Recently, data-driven models have shown promising performance …
saving and optimization. Recently, data-driven models have shown promising performance …
Spatiotemporal variations in meteorological influences on ambient ozone in China: A machine learning approach
Considering the increase in ambient ozone (O 3) levels with harmful health effects, this study
aims to evaluate the spatiotemporal variations in meteorological influences on the daily …
aims to evaluate the spatiotemporal variations in meteorological influences on the daily …