2 citations · 5 across the 9 of their papers we have counts for
9 papers
Data-Driven Soil Organic Carbon Sampling: Integrating Spectral Clustering with Conditioned Latin Hypercube Optimization
Weiying Zhao, Aleksei Unagaev, Natalia Efremova
Soil organic carbon (SOC) monitoring often relies on selecting representative field sampling locations based on environmental covariates. We propose a novel hybrid methodology that…
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
Tukey g-and-h neural network regression for non-Gaussian data
Arthur P. Guillaumin, Natalia Efremova
This paper addresses non-Gaussian regression with neural networks via the use of the Tukey g-and-h distribution.The Tukey g-and-h transform is a flexible parametric transform with…
Prediction of Sentinel-2 multi-band imagery with attention BiLSTM for continuous earth surface monitoring
Weiying Zhao, Natalia Efremova
Continuous monitoring of crops and forecasting crop conditions through time series analysis is crucial for effective agricultural management. This study proposes a framework based…
Soil nitrogen forecasting from environmental variables provided by multisensor remote sensing images
Weiying Zhao, Ganzorig Chuluunbat, Aleksei Unagaev +1
This study introduces a framework for forecasting soil nitrogen content, leveraging multi-modal data, including multi-sensor remote sensing images and advanced machine learning met…
Grapevine Disease Prediction Using Climate Variables from Multi-Sensor Remote Sensing Imagery via a Transformer Model
Weiying Zhao, Natalia Efremova
Early detection and management of grapevine diseases are important in pursuing sustainable viticulture. This paper introduces a novel framework leveraging the TabPFN model to forec…
Precision Agriculture: Crop Mapping using Machine Learning and Sentinel-2 Satellite Imagery
Kui Zhao, Siyang Wu, Chang Liu +2
Food security has grown in significance due to the changing climate and its warming effects. To support the rising demand for agricultural products and to minimize the negative imp…
Soil Organic Carbon Estimation from Climate-related Features with Graph Neural Network
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 ma…
AI for Agriculture: the Comparison of Semantic Segmentation Methods for Crop Mapping with Sentinel-2 Imagery
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 chan…