Columbia University Image Library (COIL-20): To database is available in two versions. The first, [unprocessed], consists of images for five of the objects that contain both the object and the background. The second, [processed], contains images for all of the objects in which the background has been discarded (and the images consist of the smallest square that contains the object). For formal documentation look at the corresponding compressed technical report, [gzipped].

References in zbMATH (referenced in 93 articles )

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  1. Giffon, Luc; Emiya, Valentin; Kadri, Hachem; Ralaivola, Liva: Quick-means: accelerating inference for K-means by learning fast transforms (2021)
  2. Huang, Hua; Wang, Weiwei; Lu, Chengwu; Feng, Xiangchu; He, Ruiqiang: Side-information-induced reweighted sparse subspace clustering (2021)
  3. Jing, Peiguang; Su, Yuting; Li, Zhengnan; Nie, Liqiang: Learning robust affinity graph representation for multi-view clustering (2021)
  4. Kong, Hao; Lu, Canyi; Lin, Zhouchen: Tensor Q-rank: new data dependent definition of tensor rank (2021)
  5. Sober, Barak; Aizenbud, Yariv; Levin, David: Approximation of functions over manifolds: a moving least-squares approach (2021)
  6. Budninskiy, Max; Abdelaziz, Ameera; Tong, Yiying; Desbrun, Mathieu: Laplacian-optimized diffusion for semi-supervised learning (2020)
  7. Dong, Bin; Ju, Haocheng; Lu, Yiping; Shi, Zuoqiang: CURE: curvature regularization for missing data recovery (2020)
  8. Dornaika, F.; Khoder, A.: Linear embedding by joint robust discriminant analysis and inter-class sparsity (2020)
  9. Gao, Depeng; Wu, Rui; Liu, Jiafeng; Fan, Xiaopeng; Tang, Xianglong: Finding robust transfer features for unsupervised domain adaptation (2020)
  10. Jin, Pengzhan; Lu, Lu; Tang, Yifa; Karniadakis, George Em: Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness (2020)
  11. Little, Anna; Maggioni, Mauro; Murphy, James M.: Path-based spectral clustering: guarantees, robustness to outliers, and fast algorithms (2020)
  12. Min, Yufang; Zhang, Yaonan: Exact (k)-component graph learning for image clustering (2020)
  13. Perea, Jose A.: Sparse circular coordinates via principal (\mathbbZ)-bundles (2020)
  14. Xue, Xuqian; Zhang, Xiaoqian; Feng, Xinghua; Sun, Huaijiang; Chen, Wei; Liu, Zhigui: Robust subspace clustering based on non-convex low-rank approximation and adaptive kernel (2020)
  15. Zhen, Liangli; Peng, Dezhong; Wang, Wei; Yao, Xin: Kernel truncated regression representation for robust subspace clustering (2020)
  16. Derkach, Dmytro; Ruiz, Adria; Sukno, Federico M.: Tensor decomposition and non-linear manifold modeling for 3D head pose estimation (2019)
  17. Diaz-Chito, Katerine; Martínez del Rincón, Jesús; Rusiñol, Marçal; Hernández-Sabaté, Aura: Feature extraction by using dual-generalized discriminative common vectors (2019)
  18. Ge, Shaodi; Li, Hongjun; Luo, Liuhong: Constrained dual graph regularized orthogonal nonnegative matrix tri-factorization for co-clustering (2019)
  19. Jin, Taisong; Yu, Zhengtao; Gao, Yue; Gao, Shengxiang; Sun, Xiaoshuai; Li, Cuihua: Robust (\ell_2)-hypergraph and its applications (2019)
  20. Liu, Xi; Ma, Zhengming; Niu, Guo: Mixed region covariance discriminative learning for image classification on Riemannian manifolds (2019)

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