… 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 …

… 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. …

… neural networks—seems to be the most promising area in the field of detection of forest cover
disturbances from satellite … ., Deep learning for regular change detection in Ukrainian forest …

… 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. …

… Landsat-8 imagery for the detection of active fires and burning biomass. … images from Landsat-8
satellite imagery. The proposed … The fifth study area belongs to Chernobyl, Ukraine. The …

… 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 (…

… for the use of convolutional neural networks in the fields of … for feature of extraction, I will
now introduce the area that is … at the same place as the burning (primary cremation), tumuli …

… tools such as deep learning and neural networks. As a result of … This method allows you to
cover a large amount of territory, … of displaying burned areas with the usage of satellite images …

… will increase while the area of burned forests will not decrease… satellite images and
conveniently manage forest lands [24]. … cover in Ukraine, although the area of forest land covered …

… fields of medical image analysis and autonomous driving. … of different types, windthrows,
burns, and forest roads, and … and a U-Net convolutional neural network. It is determined the …