Hamza Elkhouchlaa

Papers

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About

Hamza Elkhouchlaa is a researcher at the forefront of precision agriculture and remote sensing, specializing in the application of unmanned aerial vehicle (UAV) imagery for crop monitoring and management. His work centers on developing efficient, computer-vision-based methods for detecting and locating fruit in complex orchard environments, addressing critical challenges in agricultural automation. His most-cited paper, "Fast detection and location of longan fruits using UAV images" (2021), has garnered 52 citations, demonstrating its influence in advancing real-time, high-throughput fruit detection from aerial platforms. This contribution is notable for its practical impact on yield estimation and harvesting logistics, offering a scalable solution for tropical fruit cultivation. Elkhouchlaa’s research integrates deep learning, image processing, and geospatial analysis, bridging the gap between laboratory algorithms and field-ready applications. His work not only enhances agricultural efficiency but also supports sustainable practices by reducing manual labor and resource waste. For students and researchers in agritech, his studies provide a clear model for translating UAV data into actionable insights, making him a key figure in the growing intersection of robotics, computer vision, and smart farming.