activity
20242026
collaborators

5 papers

cs.CV2026

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

Petar Canoski, Vlatko Spasev, Ivica Dimitrovski +2

Grape leaf disease recognition is important for precision agriculture, enabling early diagnosis, timely intervention, and improved vineyard management. Although deep learning has a…

cs.LG2026

Event-Based Early Warning of Vineyard Disease Risk from Environmental Time Series

Ivica Dimitrovski, Ivan Kitanovski, Danco Davcev +2

Accurate early warning of vineyard disease risk from environmental observations is essential for timely intervention and more sustainable crop protection. However, many existing st…

cs.CV2025

Few-Shot Remote Sensing Image Scene Classification with CLIP and Prompt Learning

Ivica Dimitrovski, Vlatko Spasev, Ivan Kitanovski

Remote sensing applications increasingly rely on deep learning for scene classification. However, their performance is often constrained by the scarcity of labeled data and the hig…

cs.CV2024

Semantic Segmentation of Unmanned Aerial Vehicle Remote Sensing Images using SegFormer

Vlatko Spasev, Ivica Dimitrovski, Ivan Chorbev +1

The escalating use of Unmanned Aerial Vehicles (UAVs) as remote sensing platforms has garnered considerable attention, proving invaluable for ground object recognition. While satel…

cs.CV2024

Deep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth Observation Data

Ivica Dimitrovski, Vlatko Spasev, Ivan Kitanovski

Accurate semantic segmentation of remote sensing imagery is critical for various Earth observation applications, such as land cover mapping, urban planning, and environmental monit…