… In this paper, we proposed convolution neural networks for … remotely sensed satellite
images of the territory of Ukraine. … (agricultural fields, forest, smoke, urban, burned and other), a …

… locations on a map for civilians to use to ensure safer … the ruined area, sometimes it fails
at recognizing the whole … in historical aerial images using convolutional neural networks”. …

… multispectral images of wildfire areas from satellite Landsat 8; … The largest forest areas
were burned in 2015 and 2017 (more … It is as a new field of research within machine learning. …

… sensing using satellite imagery and aerial observation arise to … This work investigates and
employs deep neural network (… sensing illustrates ongoing advances in this field. The study of …

… In 2020, the results of works on the wind blow recognition in the forests of Western
Europe [34], and clear-cuts in Ukraine [21] using convolutional neural networks of the U-net …

… of agriculture, land use and building detection in the field of urbanization. In this study, a …
convolutional neural network for automatic burnt area detection on high-resolution aerial images…

… effective tool for addressing many tasks in this field. The modern stage of RSD development
… of fire and burned area recognition in satellite images using convolutional neural networks (…

… models that used convolutional neural network (CNN)-derived … mapping artillery craters in
Eastern Ukraine in 2014. We aim … uncultivated area that has been hit with artillery and burned. …

… burnt forest areas from Sentinel-2 imagery. The proposed algorithm uses an approach based
on convolutional neural networks (… ), which will require field validation. Another direction of …

… Rating of years by the largest amount of burned acres will be … success of convolutional
neural networks is image recognizing [… , taken from satellite to work with them as with specified …