Cuijuan Jiao

Qingdao University of Science and Technology

Papers

Total Citations

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About

Cuijuan Jiao is a researcher specializing in computer vision and deep learning, with a particular focus on industrial defect detection. Her most notable contribution is the development of a tire defect detection system based on the Faster R-CNN architecture, published in 2020. This work, which has garnered 11 citations, addresses a critical challenge in manufacturing quality control by applying advanced object detection techniques to identify flaws in tire production. Jiao’s research bridges the gap between theoretical deep learning models and practical industrial applications, demonstrating how convolutional neural networks can be optimized for real-time, high-accuracy inspection tasks. Her work is significant for its potential to reduce waste, improve safety, and automate quality assurance in the automotive industry. By adapting Faster R-CNN—a model originally designed for general object detection—to the specific domain of tire defects, Jiao has contributed to the growing field of AI-driven manufacturing. Her findings offer a scalable solution for industries seeking to integrate intelligent visual inspection systems, making her a valuable voice in applied computer vision research.