Poh Soon JosephNg

UCSI University, INTI International University

Papers

Total Citations

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About

Poh Soon JosephNg is a researcher whose work bridges the frontiers of data mining, autonomous systems, and real-time computer vision. His key research areas include applying drone technology for data-driven financial analysis in the property sector and advancing pedestrian and object detection for safety-critical applications. In his notable 2020 study, "Jomdrone: Data Mining Financial Sense in the Property Agency," JosephNg demonstrated how drones—equipped with GPS and sensors—can revolutionize property analytics, extracting actionable financial insights from aerial data. This work, cited 5 times, highlights the practical impact of robotics on industry. More recently, in 2024, JosephNg contributed to the field of autonomous safety with "Real time pedestrian and objects detection using enhanced YOLO integrated with learning complexity-aware cascades," also garnering 5 citations. This research addresses the growing demand for accurate, real-time detection in autonomous vehicles and surveillance, enhancing YOLO algorithms with complexity-aware cascades to improve reliability. Through these contributions, JosephNg is shaping how intelligent systems perceive and interact with the world, making him a valuable voice in the intersection of data science and autonomous technology.