Brahim Aksasse

About

Brahim Aksasse is a leading researcher in agricultural artificial intelligence, with a focused expertise in precision agriculture, computer vision, and automated harvesting systems. His major contributions center on developing intelligent solutions for date fruit cultivation, addressing critical challenges in food security and agricultural efficiency. Aksasse’s most impactful work includes the creation of a specialized "Date fruit detection dataset for automatic harvesting" (2023, 14 citations), which provides essential annotated imagery for training machine learning models to identify and locate dates on palm trees. Building on this foundation, he designed a "Smart Harvesting Decision System for Date Fruit Based on Fruit Detection and Maturity Analysis Using YOLO and K-Means Segmentation" (2023, 4 citations), a novel framework that combines deep learning object detection with unsupervised clustering to assess fruit ripeness in real time. This system enables automated, selective harvesting—reducing labor costs and post-harvest losses that can reach significant percentages of annual yields. Aksasse’s work directly supports the global date industry, which produces over 9 million tons annually, by translating cutting-edge AI into practical, deployable tools for farmers and agritech companies. His research exemplifies how computer vision can transform traditional agriculture into a data-driven, sustainable enterprise.

Research Focus

Key Achievements

Top Papers

1. 1
   Date fruit detection dataset for automatic harvesting

   14 citations · 2023
2. 2
   Smart Harvesting Decision System for Date Fruit Based on Fruit Detection and Maturity Analysis Using YOLO and K-Means Segmentation

   4 citations · 2023

Key Collaborators

Contact & Links