Ismail Assayad

University of Hassan II Casablanca

Papers

1

Total Citations

2

H-Index

1

About

Dr. Ismail Assayad is a researcher whose work sits at the intersection of artificial intelligence and practical, real-world problem-solving. His primary research areas include deep learning, computer vision, and intelligent systems, with a particular focus on developing deployable solutions for safety and security. His most notable contribution is the development of a face-mask detection system leveraging deep learning convolutional neural networks, published in 2021. This work, which has garnered early citations, addresses a critical need in public health and safety, demonstrating his ability to translate complex AI models into tangible tools for societal benefit. By focusing on the application of convolutional neural networks to a pressing global challenge, Dr. Assayad exemplifies how cutting-edge research can directly impact everyday life. His work is particularly relevant for students and researchers interested in the intersection of AI, public health, and computer vision, showcasing the potential of deep learning to create smart, responsive systems for a safer world.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A Face-Mask Detection System Based on Deep Learning Convolutional Neural Networks
2 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Hassan II Casablanca

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago