Skoltech
CDISE
EDSEL
Publications
EDSEL
Skoltech
CDISE
Publications
Publications
Skoltech, EDSEL
2020
2020
Shadrin, D., Pukalchik, M., Kovaleva, E., & Fedorov, M. (2020). Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils. Ecotoxicology and Environmental Safety, 194, 110410.

Gasanov, M., Petrovskaia, A., Nikitin, A., Matveev, S., Tregubova, P., Pukalchik, M., & Oseledets, I. Sensitivity analysis of soil parameters in crop model supported with high-throughput computing, ICCS, 2020

Shadrin, D., Pukalchik, M., Uryasheva, A., Rodichenko, N., & Tsetserukou, D. (2020). Hyper-spectral NIR and MIR data and optimal wavebands for detecting of apple trees diseases. arXiv preprint arXiv:2004.02325, ICLR 2020

Matvienko, I., Gasanov, M., Petrovskaia, A., Jana, R. B., Pukalchik, M., & Oseledets, I. (2020). Bayesian aggregation improves traditional single image crop classification approaches. arXiv preprint arXiv:2004.03468, ICLR 2020

Petrovskaia, A., Jana, R. B., & Oseledets, I. V. (2020). A single image deep learning approach to restoration of corrupted remote sensing products. arXiv preprint arXiv:2004.04209, ICLR 2020
2019
2019
Nikitin, A., Fastovets, I., Shadrin, D., Pukalchik, M., & Oseledets, I. (2019). Bayesian optimization for seed germination. Plant methods, 15(1), 43.

Pukalchik, M., Kydralieva, K., Yakimenko, O., Fedoseeva, E., & Terekhova, V. (2019). Outlining the potential role of humic products in modifying biological properties of the soil—a review. Frontiers in Environmental Science, 7, 80.

Pukalchik, M. A., Katrutsa, A. M., Shadrin, D., Terekhova, V. A., & Oseledets, I. V. (2019). Machine learning methods for estimation the indicators of phosphogypsum influence in soil. Journal of soils and sediments, 19(5), 2265-2276.

Jana, R. B., & Petrovskaia, A. (2019). 3D representation of soil structure using Generative Adversarial Networks. AGUFM, 2019, H31I-1835.

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