no code implementations • 27 Nov 2023 • Weiying Zhao, Natalia Efremova
Soil organic carbon (SOC) plays a pivotal role in the global carbon cycle, impacting climate dynamics and necessitating accurate estimation for sustainable land and agricultural management.
no code implementations • 21 Nov 2023 • Irina Korotkova, Natalia Efremova
Crop mapping is one of the most common tasks in artificial intelligence for agriculture due to higher food demands from a growing population and increased awareness of climate change.
no code implementations • 15 Sep 2020 • Sagar Vaze, James Foley, Mohamed Seddiq, Alexey Unagaev, Natalia Efremova
The analysis of satellite imagery will prove a crucial tool in the pursuit of sustainable development.
no code implementations • 16 Mar 2020 • Conrad James Foley, Sagar Vaze, Mohamed El Amine Seddiq, Alexey Unagaev, Natalia Efremova
Soil moisture is critical component of crop health and monitoring it can enable further actions for increasing yield or preventing catastrophic die off.
no code implementations • 5 Jul 2019 • Natalia Efremova, Dennis West, Dmitry Zausaev
The framework of the seventeen sustainable development goals is a challenge for developers and researchers applying artificial intelligence (AI).
no code implementations • 5 Jun 2019 • Natalia Efremova, Dmitry Zausaev, Gleb Antipov
We achieve this by applying satellite imagery, crop segmentation, soil classification and NDVI and soil moisture prediction on satellite data, ground truth and climate data records.
no code implementations • 13 Nov 2017 • Boris Knyazev, Roman Shvetsov, Natalia Efremova, Artem Kuharenko
In this paper we describe a solution to our entry for the emotion recognition challenge EmotiW 2017.
no code implementations • 18 Nov 2014 • Natalia Efremova, Sergey Tarasenko
We propose a novel neural network architecture for visual saliency detections, which utilizes neurophysiologically plausible mechanisms for extraction of salient regions.