Generation of the NIR spectral Band for Satellite Images with Convolutional Neural Networks

no code implementations • 13 Jun 2021 • Svetlana Illarionova, Dmitrii Shadrin, Alexey Trekin, Vladimir Ignatiev, Ivan Oseledets

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 concerning the vegetation assessment.

Colorization Generative Adversarial Network +1

Object-Based Augmentation Improves Quality of Remote Sensing Semantic Segmentation

no code implementations • 12 May 2021 • Svetlana Illarionova, Sergey Nesteruk, Dmitrii Shadrin, Vladimir Ignatiev, Mariia Pukalchik, Ivan Oseledets

To overcome these data restrictions, it is common to consider various approaches including data augmentation techniques.

Image Augmentation Object +4

Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case

1 code implementation • 24 Feb 2021 • Sergey Nesteruk, Dmitrii Shadrin, Mariia Pukalchik

Large datasets' availability is catalyzing a rapid expansion of deep learning in general and computer vision in particular.

Few-Shot Learning Image Augmentation +7

Hyper-spectral NIR and MIR data and optimal wavebands for detection of apple tree diseases

no code implementations • 5 Apr 2020 • Dmitrii Shadrin, Mariia Pukalchik, Anastasia Uryasheva, Evgeny Tsykunov, Grigoriy Yashin, Nikita Rodichenko, Dzmitry Tsetserukou

Plant diseases can lead to dramatic losses in yield and quality of food, becoming a problem of high priority for farmers.