Foundation models for generalist medical artificial intelligence

M Moor, O Banerjee, ZSH Abad, HM Krumholz… - Nature, 2023 - nature.com
The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI)
models is likely to usher in newfound capabilities in medicine. We propose a new paradigm …

Google Earth Engine and artificial intelligence (AI): a comprehensive review

L Yang, J Driscol, S Sarigai, Q Wu, H Chen, CD Lippitt - Remote Sensing, 2022 - mdpi.com
Remote sensing (RS) plays an important role gathering data in many critical domains (eg,
global climate change, risk assessment and vulnerability reduction of natural hazards …

Comparison of land use land cover classifiers using different satellite imagery and machine learning techniques

S Basheer, X Wang, AA Farooque, RA Nawaz, K Liu… - Remote Sensing, 2022 - mdpi.com
Accurate land use land cover (LULC) classification is vital for the sustainable management
of natural resources and to learn how the landscape is changing due to climate. For …

Analysis of land use and land cover using machine learning algorithms on google earth engine for Munneru River Basin, India

KN Loukika, VR Keesara, V Sridhar - Sustainability, 2021 - mdpi.com
The growing human population accelerates alterations in land use and land cover (LULC)
over time, putting tremendous strain on natural resources. Monitoring and assessing LULC …

A systematic review of applications of machine learning techniques for wildfire management decision support

K Bot, JG Borges - Inventions, 2022 - mdpi.com
Wildfires threaten and kill people, destroy urban and rural property, degrade air quality,
ravage forest ecosystems, and contribute to global warming. Wildfire management decision …

Monitoring of dynamic wetland changes using NDVI and NDWI based landsat imagery

A Ashok, HP Rani, KV Jayakumar - Remote Sensing Applications: Society …, 2021 - Elsevier
Recent initiatives using the GIS tools for map** and analysis of wetland dynamics bring
the hope for an effective wetland management. Degraded or modified wetlands are more …

Forest fire susceptibility map** with sensitivity and uncertainty analysis using machine learning and deep learning algorithms

M Rihan, AA Bindajam, S Talukdar, MW Naikoo… - Advances in Space …, 2023 - Elsevier
In the hilly region of the Western Himalayas, forest fires play a crucial role in forest
destruction and biodiversity loss. Therefore, addressing the problem of forest fires is an …

Detection of forest fire using deep convolutional neural networks with transfer learning approach

HC Reis, V Turk - Applied Soft Computing, 2023 - Elsevier
Forest fires caused by natural causes such as climate change, temperature increase,
lightning strikes, volcanic activity or human effects are among the world's most dangerous …

Investigation of fire risk zones using heat–humidity time series data and vegetation

J Rabiei, MS Khademi, S Bagherpour, N Ebadi… - Applied Water …, 2022 - Springer
Forest fires destroy these areas and have devastating and harmful socio-economic and
environmental effects. One of the methods of preventing and managing the hazards created …

Greening and browning trends of vegetation in India and their responses to climatic and non-climatic drivers

BR Parida, AC Pandey, NR Patel - Climate, 2020 - mdpi.com
It is imperative to know the spatial distribution of vegetation trends in India and its responses
to both climatic and non-climatic drivers because many ecoregions are vulnerable to global …