Yiran Feng

Tongmyong University, Dalian Polytechnic University

Papers

Total Citations

H-Index

About

Yiran Feng is a researcher at the intersection of deep learning, robotics, and intelligent automation. Their work focuses on applying advanced computer vision and control systems to solve real-world problems in biological recognition and bionic robotics. Feng’s most impactful contribution is the development of an improved Faster R-CNN framework for shellfish recognition, a pioneering application of deep learning in marine biology that has garnered 18 citations. This work addresses a critical gap by enabling multi-object detection and localization in natural underwater environments. Additionally, Feng has explored gait programming for quadruped bionic robots, designing systems that allow stable locomotion over rugged terrain through attitude adjustment and vibration isolation. Their research also includes the development of intelligent material handling robots, integrating machine vision for 2D code reading, color and shape recognition, and autonomous grasping. These projects demonstrate a consistent focus on bridging perception and action in autonomous systems. With a growing citation record and contributions to both theoretical frameworks and practical implementations, Yiran Feng is establishing a reputation for innovative, application-driven research in intelligent robotics and deep learning.