| Outlining the potential role of humic products in modifying biological properties of the soil—a review M Pukalchik, K Kydralieva, O Yakimenko, E Fedoseeva, V Terekhova Frontiers in Environmental Science 7, 80, 2019 | 80 | 2019 |
| Biochar, wood ash and humic substances mitigating trace elements stress in contaminated sandy loam soil: Evidence from an integrative approach M Pukalchik, F Mercl, V Terekhova, P Tlustoš Chemosphere 203, 228-238, 2018 | 62 | 2018 |
| The improvement of multi-contaminated sandy loam soil chemical and biological properties by the biochar, wood ash, and humic substances amendments M Pukalchik, F Mercl, M Panova, K Břendová, VA Terekhova, P Tlustoš Environmental pollution 229, 516-524, 2017 | 48 | 2017 |
| Image compression and plants classification using machine learning in controlled-environment agriculture: Antarctic station use case S Nesteruk, D Shadrin, M Pukalchik, A Somov, C Zeidler, P Zabel, ... IEEE Sensors Journal 21 (16), 17564-17572, 2021 | 44 | 2021 |
| The triad approach to ecological assessment of urban soils VA Terekhova, MA Pukalchik, AS Yakovlev Eurasian Soil Science 47, 952-958, 2014 | 30 | 2014 |
| " Триадный" подход к экологической оценке городских почв ВА Терехова, МА Пукальчик, АС Яковлев Почвоведение, 1145-1145, 2014 | 30 | 2014 |
| Using humic products as amendments to restore Zn and Pb polluted soil: a case study using rapid screening phytotest endpoint M Pukalchik, M Panova, M Karpukhin, O Yakimenko, K Kydralieva, ... Journal of soils and sediments 18, 750-761, 2018 | 29 | 2018 |
| MixChannel: Advanced augmentation for multispectral satellite images S Illarionova, S Nesteruk, D Shadrin, V Ignatiev, M Pukalchik, I Oseledets Remote Sensing 13 (11), 2181, 2021 | 27 | 2021 |
| An automated approach to groundwater quality monitoring—geospatial mapping based on combined application of Gaussian Process Regression and Bayesian Information Criterion D Shadrin, A Nikitin, P Tregubova, V Terekhova, R Jana, S Matveev, ... Water 13 (4), 400, 2021 | 24 | 2021 |
| Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils D Shadrin, M Pukalchik, E Kovaleva, M Fedorov Ecotoxicology and Environmental Safety 194, 110410, 2020 | 24 | 2020 |
| Large-scale forecasting of Heracleum sosnowskyi habitat suitability under the climate change on publicly available data D Koldasbayeva, P Tregubova, D Shadrin, M Gasanov, M Pukalchik Scientific reports 12 (1), 6128, 2022 | 23 | 2022 |
| Object-based augmentation for building semantic segmentation: Ventura and santa rosa case study S Illarionova, S Nesteruk, D Shadrin, V Ignatiev, M Pukalchik, I Oseledets Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 23 | 2021 |
| Xtremeaugment: Getting more from your data through combination of image collection and image augmentation S Nesteruk, S Illarionova, T Akhtyamov, D Shadrin, A Somov, M Pukalchik, ... IEEE Access 10, 24010-24028, 2022 | 21 | 2022 |
| Comparison of eluate and direct soil bioassay methods of soil assessment in the case of contamination with heavy metals MA Pukalchik, VA Terekhova, MM Karpukhin, VM Vavilova Eurasian soil science 52, 464-470, 2019 | 19 | 2019 |
| Deep Learning for improving the storage process: Accurate and automatic segmentation of spoiled areas on apples N Stasenko, E Chernova, D Shadrin, G Ovchinnikov, I Krivolapov, ... 2021 IEEE International Instrumentation and Measurement Technology …, 2021 | 16 | 2021 |
| Machine learning methods for estimation the indicators of phosphogypsum influence in soil MA Pukalchik, AM Katrutsa, D Shadrin, VA Terekhova, IV Oseledets Journal of Soils and Sediments 19, 2265-2276, 2019 | 16 | 2019 |
| Triad method for assessing the remediation effect of humic preparations on urbanozems MA Pukalchik, VA Terekhova, OS Yakimenko, KA Kydralieva, MI Akulova Eurasian soil science 48, 654-663, 2015 | 16 | 2015 |
| Optimization of water quality monitoring networks using metaheuristic approaches: moscow region use case E Yudina, A Petrovskaia, D Shadrin, P Tregubova, E Chernova, ... Water 13 (7), 888, 2021 | 15 | 2021 |
| Image augmentation for multitask few-shot learning: Agricultural domain use-case S Nesteruk, D Shadrin, M Pukalchik arXiv preprint arXiv:2102.12295, 2021 | 14 | 2021 |
| Sensitivity analysis of soil parameters in crop model supported with high-throughput computing M Gasanov, A Petrovskaia, A Nikitin, S Matveev, P Tregubova, ... International Conference on Computational Science, 731-741, 2020 | 14 | 2020 |
Vera TerekhovaМГУ им. М.В. Ломоносова在 soil.msu.ru 的电子邮件经过验证
