Yangwen Li
Papers
1
Total Citations
3
H-Index
1
About
Yangwen Li is a researcher advancing the intersection of computer vision and environmental sustainability, with a primary focus on intelligent waste management systems. Their most notable contribution is the development of an enhanced garbage identification and classification framework based on the YOLOv5 architecture, published in 2024. This work addresses the pressing societal challenge of waste sorting by proposing a convolutional neural network-based detection algorithm model for garbage sorting robots, demonstrating how deep learning can be practically applied to environmental problems. While the field is still emerging, this research has already garnered 3 citations, signaling growing interest in their approach. Li's work is particularly significant for its potential to automate and improve the accuracy of waste classification, a critical step toward more efficient recycling and reduced environmental pollution. By combining state-of-the-art object detection with real-world application, Yangwen Li is contributing to the development of smarter, more sustainable urban infrastructure, making their research highly relevant for students and engineers interested in applied AI for social good.
Research Focus
Key Achievements
Top Papers
- 1