Yuliang Shi

Papers

Total Citations

H-Index

About

Yuliang Shi is a researcher working at the intersection of computer vision, deep learning, and intelligent systems. His work primarily focuses on applying advanced neural network architectures to solve practical recognition and automation challenges. One of his most impactful contributions is in environmental technology, where he explored deep learning-based image recognition for automated garbage classification—a study that has garnered 18 citations and addresses the critical need for efficient waste sorting in modern society. Shi has also advanced cybersecurity through his work on CAPTCHA recognition, employing Transformer networks to improve automated text verification, a study that contributes to the ongoing arms race between security design and recognition technology. Additionally, his research extends to robotics, where he investigated path planning for Autonomous Underwater Vehicles (AUVs) in dynamic, time-varying environments, tackling a key challenge in autonomous navigation. Through these diverse contributions, Shi demonstrates a commitment to leveraging deep learning for real-world applications, from environmental sustainability to digital security and robotic autonomy.