Wei‐Chun Chen

National Yunlin University of Science and Technology

Papers

Total Citations

367

H-Index

About

Dr. Wei‐Chun Chen is a leading researcher at the intersection of artificial intelligence and environmental sustainability, whose work is transforming how we manage waste through intelligent automation. His primary research focuses on developing optimized deep learning architectures for waste classification and real-time detection, addressing one of the most pressing challenges in modern recycling systems. Chen’s seminal 2020 paper, “Recycling waste classification using optimized convolutional neural network,” has garnered 268 citations, establishing a foundational framework for applying computer vision to waste sorting. Building on this, his 2022 study on “Deep learning networks for real-time regional domestic waste detection” (99 citations) pushed the boundaries by enabling practical, on-the-ground deployment of these models in dynamic, real-world environments. Together, these contributions have significantly improved the accuracy and efficiency of automated recycling processes, reducing contamination rates and operational costs. Chen’s work is notable for its dual emphasis on algorithmic optimization and real-world applicability, bridging the gap between theoretical AI advances and tangible environmental impact. For students and researchers, his research offers a compelling model of how deep learning can be harnessed for critical societal challenges, from smart city infrastructure to circular economy initiatives.