师资队伍

桑庆兵

日期 : 2020-06-17    点击数:      
职务

基本信息:桑庆兵,博士,副教授,硕士生导师。1996年在中国地质大学(武汉)获计算机及应用获学士学位,2006年江南大学计算机应用硕士学位2013年江南大学轻工信息技术博士学位。2010.8-2011.8美国德州大学奥斯汀分校访问学者。

研究方向:主要从事机器学习、计算机视觉、图像视频质量评价和物联网技术等方面的研究与开发。

硕士生学术型研究生招生专业:计算机科学与技术

主要方向:机器学习,计算机视觉,图像/视频质量评价。

专业型研究生招生专业:计算机技术

主要方向:计算机信息管理,智能系统,软件开发与应用。

主要成果:

论文:

[1]Qingbing Sang, Chenfei Su, Lingying Zhu, Lixiong Liu, Xiaojun Wu, Alan C. Bovik, "MoNET: no-reference image quality assessment based on a multi-depth output network," J. Electron. Imaging,30(4), 043007 (2021), doi: 10.1117/1.JEI.30.4.043007.

[1]Sang Q, Cao Y, Liu L, et al. MP2020: Visual quality assessment database for macro photography images[J]. IET Image Processing, 2021.doi.org/10.1049/ipr2.12198

[3]QingBing Sang, Yunshuo Yang, Lixiong Liu, Xiaoning Song, Xiaojun Wu. Image quality assessment based on quaternion singular value decomposition.IEEE Access, 2020,8(04):75925-75935.

[4] Lixiong Liu, Jiachao Gong, Hua Huang andQingbing Sang. Blind image blur metric based on orientation-aware local patterns.Signal Processing: Image Communication, 2020, 80(01): 1156-1167.

[5] Shuyu Huang,Qingbing Sang, Qin Wu, Xiaojun Wu and Chaofeng Li. No-reference image quality assessment based on dualchannel convolutional neural network[C]//2018 International Symposium in Sensing and Instrumentation in IoT Era (ISSI), 2018: 1-5.

[6] Bin Sun, Chaofeng Li, Liling Zeng andQingbing Sang. Target Tracking Based on Collaborative Learning Kernelized Correlation Filter[C]//2018 International Symposium in Sensing and Instrumentation in IoT Era (ISSI), 2018, 1-4.

[7]Qingbing Sang, Lixiu Wu, Chaofeng Li and Xiaojun Wu.No-Reference quality assessment for multiply distorted images based on deep learning[C]//InSmart Cities Conference (ISC2), IEEE, 2017, 1-2.

[8]Qingbing Sang,Tingting Gu, Chaofeng Li and Xiaojun Wu.Stereoscopic image quality assessment via convolutional neural networks[C]//InSmart Cities Conference (ISC2), IEEE, 2017, 1-4.

[9]桑庆兵,谭红宝.极端学习四元数小波特征的立体图像质量评价.光电子·激光,2016,(06):662-669. (EI)

[10]Qingbing Sang, Xiaojun Wu, Chaofeng Li, Alan C. Bovik . Blind Image Quality Assessment using A Reciprocal Singular Value Curve.Signal Processing: Image Communication, 2014, 29(10): 1149-1157.

[11]Qingbing Sang, Xiaojun Wu, Chaofeng Li, Yin Lu. Blind Image Blur Assessment Using Singular Value Similarity and Blur Comparisons.PLOS ONE, 2014,9(9): e108073-1-6.

[12]Qingbing Sang, Huixin Qi, Xiaojun Wu, Chaofeng Li, Alan Bovik. No reference Image Blur based on singular value curve.Journal of Visual Communication and Image Representation, 2014,25(7): 1625–1630.

[13]Qingbing Sang, Xiaojun Wu, Chaofeng Li, Yin Lu. Universal Blind Image Quality Assessment using Contourlet Transform and Singular Value Decomposition.Journal of Electronic Imaging,2014,23(6): 061104-1-9.

[14]桑庆兵,梁狄林,吴小俊,李朝锋.基于支持向量回归无参考模糊和噪声图像质量评价方法.光电子.激光, 2014,25(3);595-601. (EI)

[15]桑庆兵,齐会新,吴小俊,李朝锋.基于DCT系数无参考模糊图像质量评价方法.仪器仪表学报,2013,34(11):21-26 (EI)

[16] Chaofeng Li, Yiwen Ju, Alan C. Bovik, Xiaojun Wu andQingbing Sang. No-training, no-reference image quality index using perceptual features.Optical Engineering, 2013, 52(5): 057003-1-6.

[17]桑庆兵,李朝锋,吴小俊.基于灰度共生矩阵的无参考模糊图像质量评价方法.模式识别与人工智能,2013,26(5):492-497(EI)

[18]桑庆兵,邓赵红,吴小俊.基于ε-不敏感准则和结构风险的鲁棒径向基函数神经网络学习.电子与信息学报,2012,34(6):1414-1419 (EI)

科研项目:

[1]江苏省自然科学基金面上项目,BK20171142,基于样本合成与迁移学习无参考图像质量评价模型研究,2017/12-2020/12,在研,主持

[2]江苏省产学研前瞻性联合研究项目,BY2013015-41,基于物联网的环境智能分析与监测系统,2013/12-2015/12,已结题,主持

[3]国家自然科学基金面上项目,61170120,通用无参考图像和视频质量评价方法,2012/01-2015/12,已结题,参加

[4]基于GPRS环境监控分析系统开发,企业横向开发,2007-2009,技术负责;

[5]无人水下机器人故障诊断实验系统软件,国家863项目子项目,2006-2008,主持

Emailqingbings@jiangnan.edu.cn