Artificial intelligence for remote sensing data analysis: A review of challenges and opportunities
Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …
particularly machine learning algorithms, range from initial image processing to high-level …
Artificial intelligence-based solutions for climate change: a review
L Chen, Z Chen, Y Zhang, Y Liu, AI Osman… - Environmental …, 2023 - Springer
Climate change is a major threat already causing system damage to urban and natural
systems, and inducing global economic losses of over $500 billion. These issues may be …
systems, and inducing global economic losses of over $500 billion. These issues may be …
Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a review
Atmospheric extreme events cause severe damage to human societies and ecosystems.
The frequency and intensity of extremes and other associated events are continuously …
The frequency and intensity of extremes and other associated events are continuously …
A review of machine learning for convective weather
We present an overview of recent work on using artificial intelligence (AI)/machine learning
(ML) techniques for forecasting convective weather and its associated hazards, including …
(ML) techniques for forecasting convective weather and its associated hazards, including …
Analysis, characterization, prediction and attribution of extreme atmospheric events with machine learning: a review
Atmospheric Extreme Events (EEs) cause severe damages to human societies and
ecosystems. The frequency and intensity of EEs and other associated events are increasing …
ecosystems. The frequency and intensity of EEs and other associated events are increasing …
Deep learning techniques in extreme weather events: A review
Extreme weather events pose significant challenges, thereby demanding techniques for
accurate analysis and precise forecasting to mitigate its impact. In recent years, deep …
accurate analysis and precise forecasting to mitigate its impact. In recent years, deep …
A study on the DAM-EfficientNet hail rapid identification algorithm based on FY-4A_AGRI
R Liu, H Dai, YY Chen, H Zhu, DH Wu, H Li, D Li… - Scientific Reports, 2024 - nature.com
Hail, a highly destructive weather phenomenon, necessitates critical identification and
forecasting for the protection of human lives and properties. The identification and …
forecasting for the protection of human lives and properties. The identification and …
[HTML][HTML] Modelling hail hazard over Italy with ERA5 large-scale variables
Hail is a meteorological phenomenon with adverse impacts that affects multiple socio-
economic sectors such as agriculture, renewable energy, and insurance. Nevertheless, the …
economic sectors such as agriculture, renewable energy, and insurance. Nevertheless, the …
Multi-Weather Classification using Deep Learning: A CNN-SVM Amalgamated Approach
Weather detection and multi-classification based on image processing are of great
importance in various fields such as transportation, agriculture, and energy management …
importance in various fields such as transportation, agriculture, and energy management …
A Comprehensive Review of Methods for Hydrological Forecasting Based on Deep Learning
X Zhao, H Wang, M Bai, Y Xu, S Dong, H Rao, W Ming - Water, 2024 - mdpi.com
Artificial intelligence has undergone rapid development in the last thirty years and has been
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …
widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a …