Sin-Ye Jhong

National Taipei University of Technology, National Taiwan University of Science and Technology

Papers

Total Citations

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About

Sin-Ye Jhong is a researcher at the forefront of computer vision and autonomous systems, with a focus on intelligent surveillance and navigation technologies. Their work bridges the gap between thermal imaging and deep learning, most notably through their highly cited 2019 paper on thermal-based pedestrian detection using Faster R-CNN and a region decomposition branch. This work, which has garnered 20 citations, addresses a critical challenge in nighttime surveillance by enabling robust pedestrian detection in low-light environments—a key requirement for modern video surveillance and automotive safety systems. More recently, Jhong has advanced the field of autonomous navigation with their 2025 study on learning-based heatmap-guided models for monocular visual odometry. This innovative approach overcomes the limitations of traditional feature-based and direct methods, offering improved performance in dynamic lighting and feature-sparse environments. By tackling these fundamental challenges, Jhong’s research demonstrates a clear trajectory from enhancing nighttime surveillance to enabling more reliable autonomous navigation, making significant contributions to the practical deployment of computer vision in real-world automation and robotics applications.