Several new scientific contributions have been published and presented as part of the project’s ongoing activities in computer vision, artificial intelligence, and precision agriculture, with particular emphasis on applications in olive farming during Spring 2026.

• “Cost-Aware Active Learning Framework for Efficient Small-Object Detection in Agricultural Images” Authors: Bonković, Uvodić, Musić, Papić Published in MDPI Electronics on 13th March 2026.

• “Towards Deep Learning-based Olive Yield Estimation” Authors: Kružić, Sikora, Musić, Gugić, Strikić, Šarolić, Papić Presented on 24th April 2026, at the conference Mostart 2026

• “Automatic detection of olive fruits and yield estimation” Authors: Papić, Sikora, Strikić, Šarolić, Gugić Presented on 14th April 2026, at 3rd International Scientific Conference Sustainability of European Agriculture

The published and presented works demonstrate continued advancements in the use of AI-driven and computer vision technologies for addressing agricultural problems, especially in the areas of olive fruit detection, orchard monitoring, and crop yield assessment.