研究领域

[1].深度学习
[2].图像处理
[3].模式识别
[4].压缩感知
[5].图像复原
[6].图像重建"科研项目
[1]基于深度学习技术的车辆检测与分类软件开发

近期论文

[1] 陈书贞.解小会,杨郁池,练秋生.利用多尺度卷积神经网络的图像超分辨率算法.信号处理.2018
[2] 樊晓宇.练秋生.基于双稀疏模型的压缩感知核磁共振图像重构.生物医学工程学杂志.2018
[3] 练秋生.侯亚伟.基于高斯混合模型的衍射成像算法.电子学报.2018
[4] 练秋生.Lian,Qiusheng,Li,Ying,Chen,Shuzhen.融合多种小波与全变差正则化的相位恢复算法.光学学报.2018
[5] 田野.练秋生,徐鹤.Mixed near-field and far-field source localization utilizing symmetric nested array.DIGITAL SIGNAL PROCESSING.2018
[6] 史洪印.Yang,Xiaoyan,Zhou,Qiuxiao,练秋生.SAR Slow Moving Target Imaging Based on Over-Sampling Smooth Algorithm.CHINESE JOURNAL OF ELECTRONICS.2017
[7] 田野.练秋生,刘凯.2-D angles of arrival estimation utilizing two-step weighted l1-norm penalty under nested coprime array with compressed inter-element spacing.IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences.2017
[8] 练秋生.Qi,Xiumei(1),Chen,Shuzhen(1),Shi,Baoshun(1).Single-shot Phase Imaging Algorithm Based on Structural Sparsity.Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology.2017
[9] 田野.练秋生,徐鹤.Sparse-reconstruction-based 2-D angle of arrival estimation with L-shaped array.AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS.2017
[10] Xiaoyu,Fan.练秋生.Compressed Sensing MRI With Phase Noise Disturbance Based on Adaptive Tight Frame and Total Variation.IEEE ACCESS.2017
[11] 景荣.孔令富,赵逢达,练秋生.基于同调理论的多空中机器人WSN大规模覆盖空洞修复方法.小型微型计算机系统.2017
[12] 练秋生.基于结构稀疏性的单次曝光相位成像算法.电子与信息学报.2017
[13] 练秋生.魏天姣,陈书贞,石保顺.基于全变差正则化的相位恢复算法.电子学报.2017
[14] 练秋生.Shi,Baoshun,Chen,Shuzhen.Transfer orthogonal sparsifying transform learning for phase retrieval.DIGITAL SIGNAL PROCESSING.2017
[15] 练秋生.宋爽,陈书贞,石保顺.基于高阶马尔可夫随机场及非线性压缩感知的相位恢复算法.电子学报.2017
[16] 练秋生.Object Recognition Based on Biologic Visual Mechanisms(Ei,083911595698)(386-390).CISP2008.2008
[17] 史洪印.周秋晓,杨晓炎,练秋生.SAR imaging method for sea scene target based on improved phase retrieval algorithm.Journal of Systems Engineering and Electronics.2016
[18] 练秋生.Sparse MRI reconstruction via different norms based on total variation(Ei,083911587859)(1579-1583).ICALIP 2008.2008
[19] 练秋生.李林.Image compressed sensing based on DT-CWT.Audio, Language and Image Processing, 2008. 2008. International Conference on.2008
[20] 练秋生.Image compressed sensing based on DT-CWT(Ei,083911587858)1573-1578.ICALIP 2008.2008
[21] 陈书贞.葛曼,练秋生,石保顺.基于两步图像重建的鲁棒相位恢复算法.计算机学报.2016
[22] baoshun,Shi.练秋生.Compressed sensing magnetic resonance imaging based on dictionary updating and block-matching and three-dimensional filtering regularisation.IET IMAGE PROCESSING.2016
[23] 练秋生.赵晓蕊,石保顺,陈书贞.基于卡通-纹理模型的相位恢复算法.电子与信息学报.2016
[24] 练秋生.韩敏,石保顺,陈书贞.融合解析模型和综合模型的压缩感知算法.电子学报.2016
[25] 练秋生.基于解析轮廓波变换的图像稀疏表示及其在压缩传感中的应用.电子学报.2010
[26] 练秋生.基于混合基稀疏图像表示的压缩传感图像重构.自动化学报.2010
[27] 练秋生.基于双树小波通用隐马尔可夫树模型的图像压缩感知.电子与信息学报.2010
[28] 文冬.贾培磊,练秋生,周艳红,路承彪.Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive Impairment.FRONTIERS IN AGING NEUROSCIENCE.2016
[29] 田野.练秋生,徐鹤.基于稀疏信号重构的DOA和极化角度估计算法.电子学报.2016
[30] 田野.练秋生.基于重加权l_1范数惩罚的远近场混合源定位算法.电子学报.2016
[31] 陈书贞.任占广,练秋生.基于改进暗通道和导向滤波的单幅图像去雾算法.自动化学报.2015
[32] 陈书贞.姬社平,练秋生.应用双稀疏模型和ADMM优化的图像复原.信号处理.2015
[33] 练秋生.王小娜,石保顺,陈书贞.基于多重解析字典学习和观测矩阵优化的压缩感知.计算机学报.2015
[34] 练秋生.石保顺,陈书贞.字典学习模型、算法及其应用研究进展.自动化学报.2015
[35] 练秋生.A joint reconstruction algorithm for multiple sensor data based on block Az.ast; orthogonal matching pursuit.Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology.2013
[36] 蔡德生;练秋生.蔡德生,练秋生.基于字典稀疏表示和梯度稀疏的图像盲去模糊.燕山大学学报自然科学版.2013
[37] 孙静;练秋生.孙静,练秋生.联合非均匀采样和压缩感知的图像压缩算法.信号处理.2013
[38] 练秋生.张钧芹,陈书贞.基于两级字典与分频带字典的图像超分辨率算法.自动化学报.2013
[39] 练秋生.田天,陈书贞,郭伟.基于变采样率的多假设预测分块视频压缩感知.电子与信息学报.2013
[40] 练秋生.刘芳,陈书贞.基于块A正交匹配追踪的多传感器数据联合重构算法.电子与信息学报.2013
[41] 练秋生.赵阳.基于空间-光谱字典的不完备高光谱图像重构.仪器仪表学报.2013
[42] 练秋生.张红卫,陈书贞.基于图像块整体稀疏性与流形投影的压缩成像.电子学报.2013
[43] 王艮化.练秋生.基于联合规整化约束的图像盲复原.燕山大学学报.2012
[44] 练秋生.结合字典稀疏表示和非局部相似性的自适应压缩成像算法.电子学报.2012
[45] 练秋生.基于图像块分类稀疏表示的超分辨率重构算法.电子学报.2012
[46] 练秋生.融合图像块低维流形特性与解析轮廓波稀疏性的压缩成像算法.电子与信息学报.2012
[47] 练秋生.基于卷积稀疏编码和K-SVD联合字典的稀疏表示.系统工程与电子技术.2012
[48] 练秋生.基于双密度圆对称轮廓波二元分布模型的压缩传感图像重构.计算机学报.2012
[49] 练秋生.Sparse image representation using the analytic contourlet transform and its application on compressed sensing.电子学报.2010
[50] 练秋生.Image Compressed Sensing based on universal HMT of the dual-tree wavelets.电子与信息学报.2010
[51] 练秋生.Image reconstruction for compressed sensing based on the combined sparse image representation.自动化学报.2010
[52] 郑桂芳.练秋生.基于视觉标准模型和复数小波的自然图像识别.计算机应用研究.2011
[53] 丁丽媛.练秋生.基于轮廓波局部高斯模型与全变差的彩色滤波阵列插值.计算机应用.2011
[54] 尚倩.练秋生,史培培.基于视觉特性的图像稀疏表示.计算机工程与应用.2011
[55] 李林.高彦彦,练秋生.基于小波域马尔可夫随机场模型的压缩传感图像重构.光学技术.2011
[56] 魏苗.练秋生.基于压缩传感的宽带频谱协方差感知算法.传感技术学报.2011
[57] 魏苗.练秋生.基于阈值优化的频谱感知算法.燕山大学学报.2011
[58] 练秋生.夏长城.基于双树复数小波局部高斯模型的彩色图像压缩感知.激光与光电子学进展.2011
[59] 练秋生.肖莹.基于小波树结构和迭代收缩的图像压缩感知算法研究.电子与信息学报.2011
[60] 练秋生.基于Harris角点检测器的指纹细节点提取算法.光学技术.2008