机译:基于超像素聚类和统一低秩表示的显着目标检测
Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi'an, Shaanxi 710071, China,Center for Complex Systems, School of Mechano-Electronic Engineering Xidian University, Xi'an Shaanxi 710071, China;
Center for Complex Systems, School of Mechano-Electronic Engineering Xidian University, Xi'an Shaanxi 710071, China;
Key Laboratory of Electronic Equipment Structure Design, Ministry of Education, Xidian University, Xi'an, Shaanxi 710071, China;
Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, U.K;
Salient object detection; Laplacian sparse subspace clustering; Unified low-rank representation; Primitive saliency dictionary construction; Super-pixel cluster;
机译:基于多尺度超像素和显着性传播的显着目标检测
机译:使用基于内容的图像检索在3D对象检测中基于超像素的显着性
机译:突出的对象检测采用本地树结构低秩表示和前景一致性
机译:从共同显着性检测到对象共分割:统一的多级低秩矩阵恢复方法
机译:基于稀疏和低秩的多模式聚类和识别的方法
机译:基于分数函数的癌症聚类非负面对称低秩表示图规则化方法
机译:基于超像素聚类和统一低秩表示的显着目标检测