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Author

A. Serek

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Open access Sep 2026

EXPLAINABLE MULTISPECTRAL ATTENTION NETWORK FOR SENTINEL-2 AGRICULTURAL LAND CLASSIFICATION

Accurate and transparent classification of agricultural land cover from satellite imagery is essential for operational crop monitoring. This study presents MS-AttNet, a compact convolutional network with squeeze-and-excitation channel attention for Sentinel-2 imagery using all thirteen spectral bands. On the EuroSAT be...

A. Serek, F. Abdoldina, Y. Vitulyova et al. · 0 citations
Open access Sep 2026

SEMANTIC SEGMENTATION OF AGRICULTURAL FIELD ANOMALY PATTERNS IN AERIAL IMAGES USING U-NET

Precision agriculture requires efficient monitoring of large agricultural fields with the aim that crop anomalies can be identified and spatially located as early as possible to enable targeted and timely field management. The traditional in-field inspection is time-consuming, tedious and measures only a small number o...

A. Serek, F. Abdoldina, E. Vitulyova et al. · 0 citations
Review Open access Aug 2026

From Detection to Maps: A Review of Automated Urban Tree Mapping Using UAV and High-Resolution Satellite Data

This systematic review discusses recent developments in the 2014-2026 mapping of these trees with the use of UAVs and high-resolution satellite imagery, and assesses the efficiency of deep learning models such as Convolutional Neural Networks and Vision Transformers in processing various source images.

Syndar Satbayev, D. Yedilkhan, A. Shoman et al. · 0 citations

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