10 citations · 13 across the 5 of their papers we have counts for
5 papers
Large scale cross-regional remote sensing flood monitoring framework for operative mapping and impact analysis
Ilya Novikov, Svetlana Illarionova, Ruslan Dzharkinov +6
Effective flood monitoring is critical for minimizing the impacts of flood disasters on populations and infrastructure. Yet reliable remote sensing across extensive and environment…
Generation of the NIR spectral Band for Satellite Images with Convolutional Neural Networks
Svetlana Illarionova, Dmitrii Shadrin, Alexey Trekin +2
The near-infrared (NIR) spectral range (from 780 to 2500 nm) of the multispectral remote sensing imagery provides vital information for the landcover classification, especially con…
Object-Based Augmentation Improves Quality of Remote Sensing Semantic Segmentation
Svetlana Illarionova, Sergey Nesteruk, Dmitrii Shadrin +3
Today deep convolutional neural networks (CNNs) push the limits for most computer vision problems, define trends, and set state-of-the-art results. In remote sensing tasks such as…
Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case
Sergey Nesteruk, Dmitrii Shadrin, Mariia Pukalchik
Large datasets' availability is catalyzing a rapid expansion of deep learning in general and computer vision in particular. At the same time, in many domains, a sufficient amount o…
Hyper-spectral NIR and MIR data and optimal wavebands for detection of apple tree diseases
Dmitrii Shadrin, Mariia Pukalchik, Anastasia Uryasheva +4
Plant diseases can lead to dramatic losses in yield and quality of food, becoming a problem of high priority for farmers. Apple scab, moniliasis, and powdery mildew are the most si…