机译:核/ L2,1-范数正则化的鲁棒邻域保持投影用于图像特征提取
School of Computer Science and Technology & Joint International Research Laboratory of Machine Learning and Neuromorphic Computing, Soochow University, Suzhou, China;
School of Computer Science and Technology & Joint International Research Laboratory of Machine Learning and Neuromorphic Computing, Soochow University, Suzhou, China;
Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong;
School of Computer Science and Technology & Joint International Research Laboratory of Machine Learning and Neuromorphic Computing, Soochow University, Suzhou, China;
Department of Electrical and Computer Engineering, National University of Singapore, Singapore;
Image reconstruction; Feature extraction; Two dimensional displays; Measurement; Robustness; Principal component analysis;
机译:语义分段和基于邻居像素的基于像素的脑部FMRI DataSet的位置提取:情感计算研究
机译:低阶二维邻域保留投影,可增强鲁棒图像表示能力
机译:高光谱遥感图像特征提取的半监控模糊邻域保存分析
机译:通过l2,1-范数正则化进行鲁棒分类的最佳特征选择
机译:BEMDEC:一种自适应且健壮的数字图像特征提取方法。
机译:对于具有大量特征的小型数据集使用逐步L1L2正则化和特征选择进行预测
机译:通过l2,1-范数正则化进行鲁棒分类的最佳特征选择
机译:用于特征提取和未爆弹药辨别的稳健统计和正则化