Author

I. Dimitrovski

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Preprint Sep 2026

A Multi-Dataset Benchmark of YOLO-Based Weed Detection in Precision Agriculture

Weed detection is an important component of precision agriculture, enabling site-specific weed management and reducing unnecessary herbicide use. Although deep learning methods have achieved strong results for crop and weed detection, many studies rely on single-dataset evaluation, making it difficult to assess robustn...

Hristina Zdraveska, Vlatko Spasev, Ivica Dimitrovski et al. · 0 citations

Preprint Aug 2026

A Dataset-Centric Benchmark of Deep Learning Methods for Grape Leaf Disease Classification and Detection

A dataset-centric benchmark of deep learning methods for grape leaf disease classification and detection that emphasizes dataset provenance, realistic field evaluation, annotation compatibility, and external validation for reliable vineyard disease recognition is presented.

Petar Canoski, Vlatko Spasev, I. Dimitrovski et al. · 0 citations

#machine learning Open access May 2026

Event-based early warning of vineyard disease risk from environmental time series

Accurate early warning of vineyard disease risk can support timely intervention and more targeted crop-protection decisions. However, conventional daily-status classification does not directly measure whether a model can anticipate the beginning of a new risk episode. This study investigates an event-based formulation...

I. Dimitrovski, Ivan Kitanovski, D. Davcev et al. · International Journal of Dat... · 0 citations