Yang Chen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Yang Chen has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Changjiang Wan
School of Mechanical Engineering, Xiasha Campus, Zhejiang Sci-Tech University, Hangzhou 310018, China
1 shared publication - Jiapeng Chen
College of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
1 shared publication - Xin Ru
College of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China
1 shared publication - Xiu Chen
Zhejiang Sci-Tech University Longgang Research Institute Co., Ltd., Wenzhou 325000, China
1 shared publication
Latest Publications
- Open Access
A High-Speed Real-Time Sorting Method for Fabric Material and Color Based on Spectral-RGB Feature Fusion
A method for simultaneous classification of fabric material and color based on hyperspectral imaging and visual detection is proposed. Fabric material classification is performed using hyperspectral imaging (HSI) combined with a one-dimensional convolutional neural network (1D-CNN), while fabric color recognition is achieved using an red-green-blue (RGB) camera and a color classification model. Material and color features from the same fabric sample are matched to realize synchronous classification. Experiments were conducted on three fabric materials (cotton, polyester, and cotton–polyester blend) and eight colors. At a conveyor speed of 1 m/s, the sorting success rates reach 95.0% for cotton, 97.5% for polyester, and 85.0% for cotton–polyester blended fabrics. The proposed method demonstrates reliable performance for single-material fabrics and good industrial applicability for automated fabric sorting.
Open AccessA High-Speed Real-Time Sorting Method for Fabric Material and Color Based on Spectral-RGB Feature Fusion
A method for simultaneous classification of fabric material and color based on hyperspectral imaging and visual detection is proposed. Fabric material classification is performed using hyperspectral imaging (HSI) combined with a one-dimensional convolutional neural network (1D-CNN), while fabric color recognition is achieved using an red-green-blue (RGB) camera and a color classification model. Material and color features from the same fabric sample are matched to realize synchronous classification. Experiments were conducted on three fabric materials (cotton, polyester, and cotton–polyester blend) and eight colors. At a conveyor speed of 1 m/s, the sorting success rates reach 95.0% for cotton, 97.5% for polyester, and 85.0% for cotton–polyester blended fabrics. The proposed method demonstrates reliable performance for single-material fabrics and good industrial applicability for automated fabric sorting.