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机译:基于粒子群算法的高光谱图像双线性光谱分解新算法
School of Geographical Science, South China Normal University, Guangzhou, China;
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China;
Department of Technology of Computers and Communications, Escuela Politécnica de Cáceres, University of Extremadura, Badajoz, Spain;
Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, Pavia, Italy;
School of Geographical Science, South China Normal University, Guangzhou, China;
Department of Computer and Information Engineering, Guangdong Technical College of Water Resources and Electric Engineering, Guangzhou, China;
Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, Pavia, Italy;
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China;
Optimization; Computational modeling; Hyperspectral imaging; Particle swarm optimization; Linear programming; Algorithm design and analysis;
机译:基于SALP群算法优化的非负矩阵分子的高光谱图像解密
机译:使用混合和二进制粒子群优化算法增强高光谱图像的空间分辨率。
机译:基于粒子群算法和混合编码差分进化算法的高光谱图像波段选择
机译:用于分解高光谱图像的粒子群优化算法
机译:了解空间分辨率对高光谱图像分解算法的影响。
机译:基于多目标粒子群算法和博弈论的高光谱遥感数据降维
机译:改进粒子群优化和模糊K型算法的杂交,用于高光谱图像分类
机译:高光谱图像利用和像素光谱分离的方法