Zi Jie Choong
Papers
2
Total Citations
40
H-Index
2
About
Zi Jie Choong is a researcher at the forefront of applied computer vision and smart manufacturing, specializing in making deep learning practical for resource-constrained environments. His work centers on optimizing object detection for robotic automation, particularly pick-and-place operations, by bridging the gap between high-accuracy algorithms and low-power embedded devices like the Raspberry Pi. Choong’s most cited paper, "A Comparative Analysis of Cross-Validation Techniques for a Smart and Lean Pick-and-Place Solution with Deep Learning" (2023, 36 citations), systematically evaluates how to achieve robust detection performance without relying on high-powered computers—a critical advance for autonomous vehicles and robotics. His follow-up work, "Object Detection with Hyperparameter and Image Enhancement Optimisation for a Smart and Lean Pick-and-Place Solution" (2024), further refines these methods, demonstrating how careful tuning of hyperparameters and image preprocessing can boost accuracy and efficiency in real-world manufacturing settings. By tackling the challenge of deploying deep learning on limited hardware, Choong is helping to democratize intelligent automation, making it more sustainable and accessible for lean production lines. His contributions are paving the way for smarter, greener factories where advanced AI runs on affordable, low-energy devices.
Research Focus
Key Achievements
Top Papers
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