Maria Pukalchik

According to our database, Maria Pukalchik authored at least 15 papers between 2020 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Bayesian Aggregation Improves Traditional Single-Image Crop Classification Approaches.

Ivan Matvienko, Mikhail Gasanov, Anna Petrovskaia, Maxim A. Kuznetsov, Raghavendra B. Jana, Maria Pukalchik, Ivan V. Oseledets

Sensors, 2022

XtremeAugment: Getting More From Your Data Through Combination of Image Collection and Image Augmentation.

Sergey Nesteruk, Svetlana Illarionova, Timur Akhtyamov, Dmitrii Shadrin, Andrey Somov, Mariia Pukalchik, Ivan V. Oseledets

IEEE Access, 2022

2021

MixChannel: Advanced Augmentation for Multispectral Satellite Images.

Svetlana Illarionova, Sergey Nesteruk, Dmitrii Shadrin, Vladimir Ignatiev, Maria Pukalchik, Ivan V. Oseledets

Remote. Sens., 2021

Object-Based Augmentation Improves Quality of Remote SensingSemantic Segmentation.

Svetlana Illarionova, Sergey Nesteruk, Dmitrii Shadrin, Vladimir Ignatiev, Mariia Pukalchik, Ivan V. Oseledets

CoRR, 2021

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

Sergey Nesteruk, Dmitrii Shadrin, Mariia Pukalchik

CoRR, 2021

Apple Trees Diseases Detection Through Computer Vision in Embedded Systems.

Denis Logashov, Dmitrii Shadrin, Andrey Somov, Mariia Pukalchik, Anastasia Uryasheva, Hari Prabhat Gupta, Nikita Rodichenko

Proceedings of the 30th IEEE International Symposium on Industrial Electronics, 2021

Deep Learning for Postharvest Decay Prediction in Apples.

Nikita Stasenko, Maxim Savinov, Valeriy Burlutskiy, Maria Pukalchik, Andrey Somov

Proceedings of the IECON 2021, 2021

Object-Based Augmentation for Building Semantic Segmentation: Ventura and Santa Rosa Case Study.

Svetlana Illarionova, Sergey Nesteruk, Dmitrii Shadrin, Vladimir Ignatiev, Mariia Pukalchik, Ivan V. Oseledets

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

A New Multi-objective Approach to Optimize Irrigation Using a Crop Simulation Model and Weather History.

Mikhail Gasanov, Daniil Merkulov, Artyom Nikitin, Sergey A. Matveev, Nikita Stasenko, Anna Petrovskaia, Mariia Pukalchik, Ivan V. Oseledets

Proceedings of the Computational Science - ICCS 2021, 2021

Deep learning techniques for enhancement of weeds growth classification.

Dmitrii Vypirailenko, Elizaveta Kiseleva, Dmitrii Shadrin, Mariia Pukalchik

Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2021

Deep Learning for improving the storage process: Accurate and automatic segmentation of spoiled areas on apples.

Nikita Stasenko, Elizaveta Chernova, Dmitrii Shadrin, Grigory V. Ovchinnikov, Ivan Krivolapov, Mariia Pukalchik

Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2021

2020

Bayesian aggregation improves traditional single image crop classification approaches.

Ivan Matvienko, Mikhail Gasanov, Anna Petrovskaia, Raghavendra Belur Jana, Maria Pukalchik, Ivan V. Oseledets

CoRR, 2020

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

Dmitrii Shadrin, Mariia Pukalchik, Anastasia Uryasheva, Evgeny V. Tsykunov, Grigoriy A. Yashin, Nikita Rodichenko, Dzmitry Tsetserukou

CoRR, 2020

Sensitivity Analysis of Soil Parameters in Crop Model Supported with High-Throughput Computing.

Mikhail Gasanov, Anna Petrovskaia, Artyom Nikitin, Sergey A. Matveev, Polina Tregubova, Maria Pukalchik, Ivan V. Oseledets

Proceedings of the Computational Science - ICCS 2020, 2020

Kalman Filtering for Accurate and Fast Plant Growth Dynamics Assessment.

Dmitrii Shadrin, Tatiana Podladchikova, Grigory V. Ovchinnikov, Artem L. Pavlov, Mariia Pukalchik, Andrey Somov

Proceedings of the 2020 IEEE International Instrumentation and Measurement Technology Conference, 2020