Shuangping Huang   黄双萍

Associate Professor

School of Electronic and Information 

South China University of Technology, China





Research Direction: Scene Text Analysis and Understanding, Computer VisionMachine Learning, Vocal Music Scoring (场景文本分析和理解,计算机视觉,机器学习,声乐评分)

Recent Research Focus

1. Scene Text Analysis and Understanding (场景文本分析和理解): 
    (1) Scene Text Detection(
    (2) Scene Text String Recognition (


2. Image Understanding (图像理解): 
    (1) Image Recognition and Classification(
    (2) Image Parsing (

    (3) Hyperspectral Image Analysis (高光谱图像分析); 

3. Machine Learning (机器学习): 
    (1) Deep Reinforcement Learning (

(2) Deep Convolutional Neural Network (深度卷积神经网络) . 


(3) Multiple Kernel Learning (多核学习);
(4) Online Learning (

(5) Sparsity Learning (稀疏学习);

Brief Bio

I am an Associate Professor at the School of Electronic and Information Engineer at South China University of Technology. I received my Ph.D. and M.A. degrees in Communication and Information System from SCUT, and a B.S. degree in Computer Science from Chongqing University of Posts and Telecommunications. I am currently focusing on four researches: 1) scene text analysis and understanding, 2) image classification and understanding, 3) vocal music subjective scoring, and 4) the related large scale machine learning research.


- Digital Signal Processing

Funding Status

National Nature Science Foundation of China, “Scene Text Detection and Recognition based on Deep Reinforcement Learning and Path-Signature Feature Map” (国家自然科学基金,面上,主持)

Fundamental Research Funds for the Central Universities of China“Intelligent City Oriented Big Image and Text data Recognition and Interaction” (中央高校基本科研业务费重点,主要参与)

Guangdong Province Natural Science Fund Project, “Vocal Music Scoring Method based on Multi-modal Deep Learning” (广东省自然科学基金,面上,主持)


Ph.D. Thesis

Shuangping Huang. “Study on Key Technologies of Generic Visual Object Recognition”. Ph.D. Thesis, Electronic and Information Dept., South China University of Technology, 2011.


Journals Articles and Conference Papers

1)        Ziyong Feng, Zhaoyang Yang, Lianwen Jin, Shuangping Huang*, and Jun Sun,Robust shared feature learning for script and nature identification, PRL, under review, 2016SCI indexed journal

2)        Shuangping Huang, Lianwen Jin, Kunnan Xue, Yuan Fang, Online Primal-dual Learning for a Data-dependent Multi-kernel Combination Model with Multi-class Visual Categorization Applications, Information Sciences Volume 320, 1 November 2015, Pages 75–100, SCI indexed journal

3)        Shuangping Huang, Lianwen Jin, Yunyu Li, Kunnan Xue, Long Qi, Online Multi-kernel Learning Based on a Triple Norm Regularizer for Semantic Image Classification, Mathematical Problem in EngineeringVolume 2015, SCI indexed journal

4)        Huang Shuangping, Qi Long, Ma Xu, Xue Kunnan, Wang Wenjuan, Zhu Xiaoyuan, BoSW Model Based Hyperspectral Image Analysis for Rice Panicle Blast Grading, Computers and Electronics in Agriculture, Volume 118, October 2015, Pages 167–178, SCI indexed journal

5)        Ziyong Feng, Lianwen Jina, Dapeng Tao, Shuangping Huang, DLANet A manifold-learning-based discriminative feature learning network for scene classification, Neurocomputing, Volume 157, 1 June 2015, Pages 11–21, SCI indexed journal

6)        Shuangping Huang, Lianwen Jin, Yuan Fang, Xiaoxin Wei. Online Heterogeneous Feature Fusion Machines for Visual Recognition, Neurocomputing, Volume 123, 10 January, 2014, pages 100-109, SCI indexed journal

7)        Shuangping Huang, Lianwen Jin. A new multi-label scene categorization method using color incorporated biologically inspired features and MIML SVM. ICICEL-B, v2, n2, p287-p293, April 2011, EI indexed journal

8)        Shuangping Huang, Lianwen Jin, Xiaoxin Wei. Online Heterogeneous Feature Fusion for Visual Recognition. International Conference on Data Mining LSVA Workshop 2011, EI indexed

9)        Shuangping Huang, Lianwen Jin. Enhanced Visual Categorization Performances by incorporation of simple feature into BIM features. IEEE ICIP 2010, p3865-3868, 2010, EI indexed

10)     Shuangping Huang, Lianwen Jin. A PLSA-based Semantic Bag Generator with Application to Natural Scene Classification under Multi-instance Multi-label learning frame work, ICIG 2009, p331-335, 2009, EI indexed

11)     Shuangping Huang, Xuejun Yue, Tiansheng Hong, Yuan Fang. Experiment and Research of Hyperspectral Estimation Model of Citrus Leaves Total Phosphorus Content. Transactions of the Chinese Society for Agricultural Machinery, 2013, EI indexed

12)     Huang Shuangping, Hong, Tiansheng, Yue, Xuejun, et al. Multiple Regression Analysis of Citrus Leaf N Content Using Hyperspectral Technology. Transactions of the CSAE, 2012, EI indexed journal

13)     Huang Shuangping, Yue, Xuejun, Hong, Tiansheng, Wu, Weibin, Li, Yunyu, Research of Citrus Leaves Potassium Content Prediction Model in Different Phenological Period. Journal of Jiangsu University (Natural Science Edition), 2013, EI indexed journal

14)     Huang Shuangping,Yue, Xuejun,Hong, Tiansheng,Cai, Kun, Lin, Shilun,A Hyperspectrum Based Models for Monitoring Phosphorus Content of Luogang Orange Leaf Using  Wavelet Denoising and Least Squares Support Vector Regression Analysis, Guangdong Agricultural Sciences, 2013, EI indexed journal

15)     Huang Shuangping, Qi Long, Ma Xu, Grading method of rice panicle blast severity based on hyperspectral image, Transactions of the Chinese Society of Agriculture, 2015, Ei indexed journal


Patent List

1)        黄双萍,金连文等,基于BLSTM的联机手写数学公式符号识别方法,发明专利,2015

2)        金连文,黄双萍等一种基于样本模板的数字化妆方法,发明专利,2015

3)        金连文,黄双萍等一种基于改进的引导滤波器的人脸图像图层分解方法,发明专利,2015

4)        金连文,黄双萍等一种基于多重网格近似算法的自适应区域感知蒙板生成方法,发明专利,2015

Research Interest

1)      Scene Text Analysis and Understanding (incidental scene text detection, scene text string recognition)

2)      Machine Learning (deep reinforcement learning, deep CNN, online learning, kernel learning, transfer learning, Graphical model etc.)

3)      Computer Vision (Large multi-class Large Scale Object Categorization )

4)      Vocal Music Scoring Method using Deep Learning