| YOLOv11: An Overview of the Key Architectural Enhancements R Khanam, M Hussain arXiv preprint arXiv:2410.17725, 2024 | 92 | 2024 |
| YOLOv11: An Overview of the Key Architectural Enhancements. arXiv 2024 R Khanam, M Hussain arXiv preprint arXiv:2410.17725, 0 | 44 | |
| In-Depth Review of YOLOv1 to YOLOv10 Variants for Enhanced Photovoltaic Defect Detection M Hussain, R Khanam Solar 4 (3), 351-386, 2024 | 29 | 2024 |
| A Comprehensive Review of Convolutional Neural Networks for Defect Detection in Industrial Applications R Khanam, M Hussain, R Hill, P Allen IEEE Access, 2024 | 29 | 2024 |
| What is YOLOv5: A deep look into the internal features of the popular object detector R Khanam, M Hussain arXiv preprint arXiv:2407.20892, 2024 | 10 | 2024 |
| Review of Threats in IoT Systems: Challenges and Solutions R Khanam International Journal for Research in Applied Science & Engineering …, 2023 | 5 | 2023 |
| Comparative Performance Evaluation of YOLOv5, YOLOv8, and YOLOv11 for Solar Panel Defect Detection R Khanam, T Asghar, M Hussain | | 2025 |
| PV-faultNet: Optimized CNN Architecture to detect defects resulting efficient PV production EE Zaman, R Khanam arXiv preprint arXiv:2411.02997, 2024 | | 2024 |
Muhammad Hussain FKHEALecturer in Computer Science, University of HuddersfieldEmail verificata su hud.ac.uk
