Ensembles and Cascading of Embedded Prototype Subspace Classifiers
暂无分享,去创建一个
[1] D. Opitz,et al. Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..
[2] C. V. Jawahar,et al. Improving CNN-RNN Hybrid Networks for Handwriting Recognition , 2018, 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR).
[3] Maya Krishnan,et al. Against Interpretability: a Critical Examination of the Interpretability Problem in Machine Learning , 2019, Philosophy & Technology.
[4] Roland Vollgraf,et al. Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms , 2017, ArXiv.
[5] T. Kohonen,et al. Associative recall of images , 2004, Biological Cybernetics.
[6] Paul A. Viola,et al. Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[7] Lior Rokach,et al. Ensemble-based classifiers , 2010, Artificial Intelligence Review.
[8] Jaime S. Cardoso,et al. Machine Learning Interpretability: A Survey on Methods and Metrics , 2019, Electronics.
[9] T. Kohonen,et al. The subspace learning algorithm as a formalism for pattern recognition and neural networks , 1988, IEEE 1988 International Conference on Neural Networks.
[10] Dorin Comaniciu,et al. Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[11] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[12] E. Oja,et al. Fast adaptive formation of orthogonalizing filters and associative memory in recurrent networks of neuron-like elements , 1976, Biological Cybernetics.
[13] T. Kohonen,et al. A principle of neural associative memory , 1977, Neuroscience.
[14] Anil K. Jain,et al. Data clustering: a review , 1999, CSUR.
[15] Rui Xu,et al. Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.
[16] Gernot A. Fink,et al. PHOCNet: A Deep Convolutional Neural Network for Word Spotting in Handwritten Documents , 2016, 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR).
[17] Mats Lind,et al. Embedded Prototype Subspace Classification: A Subspace Learning Framework , 2019, CAIP.
[18] João Gama,et al. Cascade Generalization , 2000, Machine Learning.
[19] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[20] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[21] Larry D. Hostetler,et al. The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.
[22] Paul Shapshak. Artificial Intelligence and brain , 2018, Bioinformation.
[23] Francisco Herrera,et al. Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI , 2020, Inf. Fusion.
[24] Luc Vincent,et al. Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..
[25] Shigeaki Watanabe,et al. Subspace method to pattern recognition , 1973 .
[26] Guang-Zhong Yang,et al. XAI—Explainable artificial intelligence , 2019, Science Robotics.
[27] Alex Lamb,et al. Deep Learning for Classical Japanese Literature , 2018, ArXiv.
[28] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.
[29] Gregory Cohen,et al. EMNIST: an extension of MNIST to handwritten letters , 2017, CVPR 2017.
[30] Jos B. T. M. Roerdink,et al. The Watershed Transform: Definitions, Algorithms and Parallelization Strategies , 2000, Fundam. Informaticae.
[31] Anders Hast,et al. A short feature vector for image matching: The Log-Polar Magnitude feature descriptor , 2017, PloS one.
[32] C. V. Jawahar,et al. Word Spotting and Recognition Using Deep Embedding , 2018, 2018 13th IAPR International Workshop on Document Analysis Systems (DAS).