姓　名：陈欢
　　职　称：讲师
　　办公室：
　　电　话：
　　邮　箱：huanchen@nwafu.edu.cn

　　
基本信息
　　陈欢，男，河南新乡人，2019年6月毕业于西安电子科技大学人工智能学院，获工学博士学位。2019年7月入职西北农林科技大学信息工程学院，讲师。研究方向进化计算/深度学习/遥感图像变化检测。目前在Neurocomputing，Journal of Computational and Theoretical Nanoscience，Journal of Applied Mathematics，计算机应用等期刊发表多篇文章，担任IEEE Trans. on Journal of Selected Topics in Applied Earth Observations and Remote Sensing, SCIENCE CHINA Information Sciences, International Journal of Pattern Recognition and Artificial Intelligence等期刊审稿人。


　　
研究方向
进化计算
深度学习
遥感图像变化检测

　　
开设课程

　　
学术成果
1. Huan Chen, Licheng Jiao, Miaomiao Liang, Shuyuan Yang, Biao Hou. Fast Unsupervised Deep Fusion
Network for Change Detection of Multitemporal SAR Images [J]. Neurocomputing, 2018, 332: 56-70.
2. Zhou Y, Huan Chen, Zhou G. Invasive weed optimization algorithm for optimization no-idle flow shop
scheduling problem [J]. Neurocomputing, 2014, 137: 285-292.
3.Huan Chen, Yongquan Zhou, Sucai He, Peigang Guo. Invasive weed optimization algorithm for solving
permutation flow-shop scheduling problem [J]. Journal of Computational and Theoretical Nanoscience,
2013, 10(3): 708-713.
4.Huan Chen, Yongquan Zhou, Peigang Guo, Xinxin Ouyang. A hybrid invasive weed optimization with
feasibility-based rule for constrained optimization problem [J]. Przegl?d Elektrotechniczny, 2013, 89(4):
160-167.
5. Yongquan Zhou, Qifang Luo, Huan Chen. A discrete invasive weed optimization algorithm for solving
traveling salesman problem [J]. Neurocomputing, 2015, 151: 1227-1236.
6. Yongquan Zhou, Qifang Luo, Huan Chen. A novel differential evolution invasive weed optimization
algorithm for solving nonlinear equations systems [J]. Journal of Applied Mathematics, 2013,
2013:1-18.
7.Huan Chen, Licheng Jiao, Fang Liu, Shuyuan Yang, Biao Hou. Learning Spatial-Temporal Features via
a Recurrent Convolutional Siamese Auto-Encoder for SAR Image Change Detection [J]. IEEE
Transactions on Geoscience and Remote Sensing, Undergoing Review.
8. Licheng Jiao, Miaomiao Liang, Huan Chen, Shuyuan Yang, Hongying Liu, Xianghai Cao. Deep fully
convolutional network-based spatial distribution prediction for hyperspectral image classification [J].
IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(10): 5585-5599.
9.陈欢，周永权，赵光伟. 基于混沌序列的多种群入侵杂草算法 [J]. 计算机应用，2012，第32 卷，
第7 期，1958-1961.

　　
在读学生

　　
毕业学生