Youssef Ounejjar
Papers
1
Total Citations
3
H-Index
1
About
Youssef Ounejjar is a researcher whose work sits at the intersection of artificial intelligence and precision agriculture, with a particular focus on deep learning for crop and weed identification. His most-cited paper, "The Identification of Weeds and Crops Using the Popular Convolutional Neural Networks" (2023), has garnered 3 citations, marking an early but promising contribution to the field. In this work, Ounejjar explores how convolutional neural networks (CNNs) can be leveraged to distinguish between crops and weeds in agricultural settings—a critical step toward reducing herbicide use and enabling automated, sustainable farming. By evaluating popular CNN architectures, his study provides a practical benchmark for researchers and practitioners aiming to deploy computer vision in real-world field conditions. While his citation count is modest, the relevance of his research to pressing global challenges in food security and environmental sustainability positions him as an emerging voice in agricultural AI. Ounejjar’s work is particularly valuable for students and researchers looking to understand the application of deep learning in agronomy, offering a clear entry point into the growing field of smart farming.
Research Focus
Key Achievements
Top Papers
- 1