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 84 articles )

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  1. Sober, Barak; Aizenbud, Yariv; Levin, David: Approximation of functions over manifolds: a moving least-squares approach (2021)
  2. Budninskiy, Max; Abdelaziz, Ameera; Tong, Yiying; Desbrun, Mathieu: Laplacian-optimized diffusion for semi-supervised learning (2020)
  3. Dong, Bin; Ju, Haocheng; Lu, Yiping; Shi, Zuoqiang: CURE: curvature regularization for missing data recovery (2020)
  4. Little, Anna; Maggioni, Mauro; Murphy, James M.: Path-based spectral clustering: guarantees, robustness to outliers, and fast algorithms (2020)
  5. Min, Yufang; Zhang, Yaonan: Exact (k)-component graph learning for image clustering (2020)
  6. Perea, Jose A.: Sparse circular coordinates via principal (\mathbbZ)-bundles (2020)
  7. 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)
  8. Diaz-Chito, Katerine; Martínez del Rincón, Jesús; Rusiñol, Marçal; Hernández-Sabaté, Aura: Feature extraction by using dual-generalized discriminative common vectors (2019)
  9. Ge, Shaodi; Li, Hongjun; Luo, Liuhong: Constrained dual graph regularized orthogonal nonnegative matrix tri-factorization for co-clustering (2019)
  10. Jin, Taisong; Yu, Zhengtao; Gao, Yue; Gao, Shengxiang; Sun, Xiaoshuai; Li, Cuihua: Robust (\ell_2)-hypergraph and its applications (2019)
  11. Liu, Xi; Ma, Zhengming; Niu, Guo: Mixed region covariance discriminative learning for image classification on Riemannian manifolds (2019)
  12. Ordozgoiti, Bruno; Mozo, Alberto; López de Lacalle, Jesús García: Regularized greedy column subset selection (2019)
  13. Rashmi, Manazhy; Sankaran, Praveen: Optimal landmark point selection using clustering for manifold modeling and data classification (2019)
  14. Teng, Yueyang; Yao, Yudong; Qi, Shouliang; Li, Chen; Xu, Lisheng; Qian, Wei; Fan, Fenglei; Wang, Ge: A novel framework for the NMF methods with experiments to unmixing signals and feature representation (2019)
  15. Zou, Cuiming; Tang, Yuan Yan; Wang, Yulong; Luo, Zhenghua: Huber collaborative representation for robust multiclass classification (2019)
  16. Liu, Ying; Xu, Zhen; Li, Chunguang: Online semi-supervised support vector machine (2018)
  17. Pradhan, Jitesh; Kumar, Sumit; Pal, Arup Kumar; Banka, Haider: Texture and color visual features based CBIR using 2D DT-CWT and histograms (2018)
  18. Vural, Elif; Guillemot, Christine: A study of the classification of low-dimensional data with supervised manifold learning (2018)
  19. Wang, Jing; Wang, Lidong; Liu, Xiaodong; Ren, Yan; Yuan, Ye: Color-based image retrieval using proximity space theory (2018)
  20. Bohi, Amine; Prandi, Dario; Guis, Vincente; Bouchara, Frédéric; Gauthier, Jean-Paul: Fourier descriptors based on the structure of the human primary visual cortex with applications to object recognition (2017)

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