Yuting Tang
Papers
1
Total Citations
1
H-Index
1
About
Dr. Yuting Tang is a leading researcher in intelligent robotics and industrial automation, specializing in advanced computer vision and deep learning for precise object manipulation. Their most significant contribution is the development of an improved Mask R-CNN framework for robot target classification and localization, directly addressing critical challenges in industrial settings—namely, the detection of small and irregularly shaped workpieces that traditional algorithms frequently miss or misclassify. This work, published in 2025, has already garnered attention with 1 citation, reflecting its immediate relevance to the field. By enhancing detection accuracy and segmentation performance, Dr. Tang’s research bridges the gap between theoretical deep learning models and practical robotic applications, offering robust solutions for automated manufacturing and quality control. Their work is pivotal for advancing the reliability of vision-guided robotic systems, making them more adaptable to complex, real-world industrial environments. Dr. Tang’s contributions are essential reading for researchers and engineers seeking to push the boundaries of robot perception and autonomous manipulation.
Research Focus
Key Achievements
Top Papers
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