个人简介
1 基本信息
姓 名： 邹东升
性 别： 男
招生信息： 年度招收硕士3名，招收计算机、数学等专业。
2 个人简介：
工学博士，博士后，2002年获日本电气通信大学计算机系统结构专业联合培养硕士学位，2009年获重庆大学计算机软件与理论专业博士学位， 2010－2012年重庆大学控制科学与工程流动站从事博士后研究工作。先后主持国家自然科学基金1项，重庆市自然科学基金1项，中国博士后科学基金1项，中央高校基本科研业务费科研专项项目3项，主研科技部国家重大专项项目1项。近年在JOURNAL OF COMPUTATIONAL CHEMISTRY、Journal of Computers、Journal of Information and computational science、Advances in Intelligent and Soft Computing等国外知名学术期刊及会议上发表SCI/EI学术论文20余篇，单篇SCI他引频次最高为95次。
专利
国家发明专利:基于VTLP数据增强剂多尺度时频域空洞卷积模型的语音情感识别方法,受理,.中国.201910138946.7[P].2019.
项目
1. 国家自然科学基金面上项目，71471023，2015/01-2018/12，主研.
2. 国家自然科学基金青年项目，61309013，2014/01-2016/12，主持.
3. 重庆市科技计划项目基础与前沿研究计划一般项目，cstc2014jcyjA40042，2014/08-2017/06，主持.
4. 中国博士后科学基金面上资助项目，20110490807，2011/05-2013/06，主持.
5. 中央高校基本科研业务费面上项目，CDJPY12180001，2012/12-2014/11月，主持。
6. 科技部国家重大专项项目，2008ZX07315-001，2009/07-2011/12，子课题主持.
近期论文
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论文
[1] Wei TANG, Dongsheng ZOU*, Su YANG, Jing SHI, Jingpei DAN and Guowu SONG. A Two-Stage Approach for Automatic Liver Segmentation with Faster R-CNN and DeepLab[J]. Neural Computing and Applications, 32(11): 6769-6778, 2020.( JCR Q1)
[2] Dandan Jiang, Dongsheng ZOU*, Zhipeng Deng and Jingpei DAN. Contextual multimodal sentiment analysis with information enhancement(C). CISAI2019.
[3] Wei Tang, Dongsheng Zou*, Jing Shi. DSL: Automatic Liver Segmentation with Faster R-CNN and DeepLab. International Conference on Artificial Neural Networks, 2018.
[4] Yafeng Niu, Dongsheng Zou*, Yadong Niu, Zhongshi He and Hua Tan. Improvement on Speech Emotion Recognition Based on Deep Convolutional Neural Networks (C). 2018 International Conference on Computing and Artificial Intelligence, 2018.
[5] Yinghao Li, Zhongshi He*, Hao Zhu, Dongsheng Zou, Weiwei Zhang. A coarse-to-fine scheme for groupwise registration of multisensor images[J]. International Journal of Advances Robotics Systems, 2017. (SCI)
[6] Baojun Niu, Dongsheng Zou*, Yafeng Niu. A Stacked Denoising Autoencoders Based Collaborative Approach for Recommender System [C]. International Symposium on Parallel Architecture, Algorithm and Programming. Springer, Singapore, 2017:172-181.
[7]姚平平,邹东升,牛宝君.基于用户偏好和项目属性的协同过滤推荐算法.计算机系统应用,2015,24(7): 15-21.
[8]王小恒,邹东升.一种粒子群结合遗传算法（PSO-GA）的云计算任务调度方法.世界科技研究与发展, 2014, 36(2): 111-115.
[9] Belay G Gebeyehu*, Zhongshi He,Dongsheng Zou. Software process management assessment towards CMM a systematic approach to optimize internal process improvement [J]. Advances in intelligent and soft computing, Vol. 114, pp. 499-505, 2012.
[10]刘俊,邹东升.基于主题特征的关键词抽取.计算机应用研究, 2012, 29(11): 4224-4227.
[11]Dongsheng Zou*,Zhongshi He, Jingyuan He, Yuxian Xia. Supersecondary structure prediction using Chou’s pseudo amino acid composition [J]. Journal of Computational Chemistry, Vol.32, No.2, pp.271-278, 2011.
[12] Donghsheng Zou*, Zhongshi He, Jingyuan He, Yuan Yan. Using an ensemble of support vector machine classifiers to predict protein supersecondary structural motifs [J]. Journal of Computers, Vol. 6, No. 10, pp. 2053-2059, 2011.
[13] Shaobo Zhong,Dongsheng Zou*. Web page classification using an ensemble of support vector machine classifiers [J]. Journal of Networks, Vol. 6, No. 11, pp. 1625-1630, 2011.
[14]何静媛*,邹东升,何中市, RNA二级结构预测的自适应鱼群算法模型,系统仿真学报,第22卷,第6期, 1370-1374页, 2010.
[15] Dongsheng Zou*, Zhongshi He, Jingyuan He. β-hairpin prediction with quadratic discriminant analysis using diversity measure [J]. Journal of Computational Chemistry, Vol.30, No.14, pp.2277-2284, 2009.
[16] Donghsheng Zou*, Zhongshi He, Jingyuan He, Xiaofeng Huang. β-hairpin prediction of proteins with Support Vector Machine using diversity measure [J]. Journal of Information & Computational Science, Vol. 6, No. 2, pp. 813-820, 2009.
[17] Dongsheng Zou*, Zhongshi He, XiaoFeng Huang, Yuxian Xia. Protein secondary structure prediction using Support Vector Machine with five data encoding approaches. Journal of Computational Information Systems, Vol.5, No. 4, pp. 1153-1158, 2009.
[18] Jingyuan He*, Zhongshi He,Dongsheng Zou. A BP Neural Network Method for RNA Secondary Structure Prediction based on ENSSEL Labels [J]. Journal of Information & Computational Science, Vol. 6, No. 2, pp. 569-576, 2009.
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