6 papers
A Multi-Dataset Benchmark of YOLO-Based Weed Detection in Precision Agriculture
Hristina Zdraveska, Vlatko Spasev, Ivica Dimitrovski +2
Weed detection is an important component of precision agriculture, enabling site-specific weed management and reducing unnecessary herbicide use. Although deep learning methods hav…
Towards Practical Precision Agriculture: Real-Time Fruit Detection and Video Analytics on Embedded Edge Hardware
Ivica Dimitrovski, Vlatko Spasev, Ivan Kitanovski +2
Static-image benchmarks do not capture the computational and temporal requirements of practical orchard video analytics. This study presents an end-to-end framework for real-time f…
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…
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…
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…
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…