Shuo Meng

Shuo Meng

PhD candidate of Biomedical Engineering.

City University of Hong Kong

Introduction

Shuo Meng is a PhD candidate of Biomedical Engineering at City University of Hong Kong. He aims to solve the practical engineering problems. For example, he leads the “fabric recognition” project (”织识“), which is using in the actural production and is highly praised.

Although his major is not computer science, he studied it systematically out of a strong passion. He used deep learning and other computer technologies to solve problems in Textile area, such as fabric defect detection, fabric smoothness evaluation, fabric images style transfer, fabric simulation, etc .

Shuo Meng is now working for medical signal processing under Prof. Hu Jinlian.

Download my resumé.

Interests
  • Medical Signal Processing
  • Deep Learning
  • Transfer Learning
  • Computer Vision
  • Software Development
  • (Full-stack, Mobile, Desktop)

Education

 
 
 
 
 
City University of Hong Kong
City University of Hong Kong
Aug 2021 – Present Hong Kong

Degree: PhD candidate of Biomedical Engineering

GPA: Not Applicable

 
 
 
 
 
Jiangnan University (National " Project 211" University)

Degree: Master of Textile Engineering

GPA: 86.8 out of 100, ranking top 5%

 
 
 
 
 
Jiangnan University (National " Project 211" University)

Degree: Bachelor of Textile Engineering (Minor in International Economics and Trade)

GPA: 3.58 out of 4, ranking top 5%

Programing Skills

Java

70%

Python

80%

HTML+JS+CSS

70%

Research Skills

Programming:

  • Java, Python, MATLAB, C#, JavaScript, CSS, HTML, SQL, etc.

Frameworks:

  • Springboot, SpingMVC, Mybatis, Maven, Redis, Django, Keras, TensorFlow, Pytorch, ES6, Vue, JQuery, Layui, uni-app, MySQL, SQLite, Git, etc.

Languages:

  • Mandarin (Native), English (Fluent), IELTS 7 (Listening, Reading, Writing and Speaking: 8, 7, 6.5, 6.5).

Certificates:

  • Certificate of National Computer II, Chinese National Scholarship, Excellent postgraduate of Jiangnan University.

Research Experience

 
 
 
 
 
Recognition of Fabric Structure Parameters Based on Deep Neural Networks
Jan 2019 – Mar 2021 Jiangnan University

A graduate project granted under the Postgraduate Research & Practice Innovation of Jiangsu Province 1062050205206039.

The project adopted a wireless device and established a fabric images dataset with elaborated structure parameters. Presented a multi-task and multi-scale convolutional neural network (MTMSnet) to recognize the fabric density, weaving pattern, reaching under 2% and 10% error respectively.

The project is called “织识”， which is now online. Some of the source can be found in my “Github”

 
 
 
 
 
Fabric Defect Detection Based on Deep Neural Networks
Jan 2019 – Mar 2021 Jiangnan University

A project came from the competition of Tianchi 2019 Guangdong Intelligent Identification of Cloth Defects.

Proposed a two-stage strategy to do local defect prediction and global defect recognition by using the Inception-VI model and LeNet-5 model, reaching 93.2% accuracy based on our cropped dataset.

 
 
 
 
 
Objective Evaluation of Fabric Smoothness Based on Deep Neural Networks
Jan 2019 – Mar 2021 Jiangnan University

The decoloration problem was solved by a paired image-to-image translation model built by conditional generative adversarial networks (GAN), which is also promising for fabric defect detection and other problems.

An ordinal classification framework based on label noise estimation (OCF-LNE) to objectively evaluate the fabric smoothness appearance degree. In this project, I helped to establish the dataset and the paper can be found in https://doi.org/10.1109/ACCESS.2019.2959705

 
 
 
 
 
Fabric Images Style Transfer Based on Deep Neural Networks
Jan 2019 – Mar 2021 Jiangnan University
A genetic algorithm (GA) and A style-generative adversarial networks (StyleGAN) based method was adopted to realize the color transfer of colored spun yarned fabrics. The effect of the fabric images style transfer can be found in my GitHub
 
 
 
 
 
Development of ERP System in Textile Production Enterprises
Jan 2019 – Mar 2021 Jiangnan University

A graduate project which was a web-based production management system specially designed for textile production enterprises, which also involved data-collecting devices based on Arduino to monitor weaving process in real-time.

Responsible for the back-end and front-end development and the thesis “Development of APS Software for Scheduling of Multi-varieties Weaving Production” won the “Excellent Theses of Jiangnan University”.

The source code can be found in my GitHub. A demo project can be found in http://www.jntex.cn:88/

Practice Experience

Nanjing Riyixin Clothing Technology Co., Ltd. (Start-ups)
Jul 2019 – Sep 2019
Responsible for front-end development of the company’s financial management system. Familiar with REST development and frameworks such as Springboot, Layui, uni-app, etc.
See certificate
Danyang Dansheng Textile Co., Ltd. (Top 500 private textile enterprises in China)
Jun 2018 – Jun 2019
Participated in the ERP system development. Familiar with SSM framework and understand the RPC framework.
See certificate
Shandong Lutai Textile Co., Ltd. (A and B listed companies)
Jun 2017 – Nov 2017
An internship in Scheduling Section. Familiar with the whole process of textile production including spinning, bleaching and dyeing, weaving, arranging, clothing, etc.
See certificate

Publications

Articles:

  1. Shuo Meng, Ruru Pan, Weidong Gao, Jian Zhou, Jingan Wang, Wentao He. A multi-task and multi-scale convolutional neural network for automatic recognition of woven fabric pattern. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-020-01607-9
  2. Shuo Meng, Jingan Wang, Ruru Pan, Weidong Gao, Jian Zhou, Wentao He. Recognition of the layout of colored yarns in yarn-dyed fabrics. Textile Research Journal. https://doi.org/10.1177/0040517520932830
  3. Shuo Meng, Ruru Pan, Weidong Gao, Jian Zhou, Jingan Wang, Wentao He. Woven Fabric Density Measurement by Using Multi-Scale Convolutional Neural Networks. IEEE Access. 2019; 7: 75810-21. https://doi.org/10.1109/access.2019.2922502
  4. Shuo Meng, Ruru Pan, Weidong Gao, Jingan Wang, Wentao He, Lijun Zhou. Research on weaving scheduling using main objective evolutionary genetic algorithm. Journal of Textile Research, 2019, 40(8): 169-174. https://doi.org/10.13475/j.fzxb.20180505606
  5. Shuo Meng, Xuwen Xia, Ruru Pan, Jian Zhou, Lei Wang, Weidong Gao. Detection of fabric density uniformity based on convolutional neural network. Journal of Textile Research, 2021, 42(2): 101-106. https://doi.org/10.13475/j.fzxb.20201008406
  6. Shuo Meng, Xuwen Xia, Wentao He, Jun Xiang, Ruru Pan, Weidong Gao. Automatic Recognition of Woven Fabric Structure Parameters——A Review. Artificial Intelligence Review. (Minor Revision)
  7. Shuo Meng, Wentao He, Jingan Wang, Jun Xiang, Ruru Pan, Weidong Gao. Gender Classification in Crowd Based on a Cascaded Neural Network. Soft Computing. (Under review)
  8. Zhongjian Li, Shuo Meng, Lei Wang, Ning Zhang, Weidong Gao. Intelligent recognition of the patterns of yarn-dyed fabric based on LSRT images. Journal of Engineered Fibers and Fabrics. 2019; 14: 1558925019840659. https://doi.org/10.1177/1558925019840659
  9. Jingan Wang, Shuo Meng, Kuangjun Shi, Lei wang, Fengxin Sun, Ruru Pan, Weidong Gao. Objective evaluation of fabric smoothness appearance with an ordinal classification framework based on label noise estimation. Textile Research Journal. http://dx.doi.org/10.1177/0040517520939574.
  10. Jun Xiang, Jingan Wang, Jian Zhou, Shuo Meng, Ruru Pan and Weidong Gao. Fabric defect detection based on a deep convolutional neural network using a two-stage strategy. Textile Research Journal. https://doi.org/10.1177/0040517520935984
  11. Ning Zhang, Ruru Pan, Lei Wang, Shuo Meng, Weidong Gao. Pattern retrieval of yarn-dyed plaid fabric based on modified interactive genetic algorithm. Color Research and Application. http://dx.doi.org/10.1002/col.22538
  12. Wentao He, Ruru Pan, Weidong Gao, Shuo Meng, Jingan Wang. Weaving scheduling based on an improved ant colony algorithm. Textile Research Journal. https://doi.org/10.1177/0040517520948896.
  13. Ning Zhang, Qun hu, Shuo Meng, Ruru Pan. Appearance Transfer for the Fabric of Colored Spun Yarn Based on Image Color Transfer. Textile Research Journal. (Accpeted).

Patents:

  1. Ruru Pan, Shuo Meng, Weidong Gao, Jian Zhou. A method based on convolutional neural networks for the recognition of woven fabric structure parameters. Filing No. 2020104863316, PRC Invention Patent (2020).
  2. Ruru Pan, Shuo Meng, Weidong Gao, Jian Zhou. An online portable system for the recognition of woven fabric structure parameters. Filing No. 2020104863195, PRC Invention Patent (2020).

Contact