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Francisco Escolano: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Antonio Peñalver Benavent, Juan Manuel Sáez, Francisco Escolano
    An Entropy Maximization Approach to Optimal Model Selection in Gaussian Mixtures. [Citation Graph (0, 0)][DBLP]
    CIARP, 2003, pp:432-439 [Conf]
  2. Miguel Angel Lozano, Francisco Escolano
    Two New Scale-Adapted Texture Descriptors for Image Segmentation. [Citation Graph (0, 0)][DBLP]
    CIARP, 2003, pp:137-144 [Conf]
  3. Miguel Angel Lozano, Francisco Escolano
    Regularization Kernels and Softassign. [Citation Graph (0, 0)][DBLP]
    CIARP, 2004, pp:320-327 [Conf]
  4. Juan Manuel Sáez, Antonio Peñalver Benavent, Francisco Escolano
    Compact Mapping in Plane-Parallel Environments Using Stereo Vision. [Citation Graph (0, 0)][DBLP]
    CIARP, 2003, pp:659-666 [Conf]
  5. Miguel Cazorla, Francisco Escolano, Domingo Gallardo, Ramón Rizo
    Bayesian Models for Finding and Grouping Junctions. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 1999, pp:70-82 [Conf]
  6. Miguel Angel Lozano, Francisco Escolano
    EM Algorithm for Clustering an Ensemble of Graphs with Comb Matching. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 2003, pp:52-67 [Conf]
  7. Francisco Escolano, Miguel Cazorla, Domingo Gallardo, Ramón Rizo
    Deformable Templates for Tracking and Analysis of Intravascular Ultrasound Sequences. [Citation Graph (0, 0)][DBLP]
    EMMCVPR, 1997, pp:521-534 [Conf]
  8. Miguel Angel Lozano, Francisco Escolano
    ACM Attributed Graph Clustering for Learning Classes of Images. [Citation Graph (0, 0)][DBLP]
    GbRPR, 2003, pp:247-258 [Conf]
  9. Miguel Angel Lozano, Francisco Escolano
    Protein Classification with Kernelized Softassign. [Citation Graph (0, 0)][DBLP]
    GbRPR, 2005, pp:332-341 [Conf]
  10. Miguel Angel Lozano, Francisco Escolano
    Local Entropic Graphs for Globally-Consistent Graph Matching. [Citation Graph (0, 0)][DBLP]
    GbRPR, 2005, pp:342-351 [Conf]
  11. Miguel Angel Lozano, Francisco Escolano
    Recognizing Indoor Images with Unsupervised Segmentation and Graph Matching. [Citation Graph (0, 0)][DBLP]
    IBERAMIA, 2002, pp:933-942 [Conf]
  12. Miguel Angel Lozano, Francisco Escolano
    Structural Recognition with Kernelized Softassign. [Citation Graph (0, 0)][DBLP]
    IBERAMIA, 2004, pp:626-635 [Conf]
  13. Juan Manuel Sáez, Francisco Escolano
    Monte Carlo Localization in 3D Maps Using Stereo Vision. [Citation Graph (0, 0)][DBLP]
    IBERAMIA, 2002, pp:913-922 [Conf]
  14. Antonio Peñalver Benavent, Francisco Escolano, Juan Manuel Sáez
    Color Image Segmentation Through Unsupervised Gaussian Mixture Models. [Citation Graph (0, 0)][DBLP]
    IBERAMIA-SBIA, 2006, pp:149-158 [Conf]
  15. Francisco Escolano, Miguel Cazorla, Domingo Gallardo, Faraón Llorens, Rosana Satorre, Ramón Rizo
    A Combined Probabilistic Framework for Learning Gestures and Actions. [Citation Graph (0, 0)][DBLP]
    IEA/AIE (Vol. 2), 1998, pp:658-667 [Conf]
  16. Miguel Angel Lozano, Francisco Escolano
    A Significant Improvement of Softassign with Diffusion Kernels. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2004, pp:76-84 [Conf]
  17. Antonio Peñalver Benavent, Francisco Escolano, Juan Manuel Sáez
    Two Entropy-Based Methods for Learning Unsupervised Gaussian Mixture Models. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2006, pp:649-657 [Conf]
  18. Miguel Cazorla, Francisco Escolano, Domingo Gallardo, Ramón Rizo
    Junction detection and grouping with probabilistic edge models and Bayesian A. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2002, v:35, n:9, pp:1869-1881 [Journal]
  19. Miguel Angel Lozano, Francisco Escolano
    Protein classification by matching and clustering surface graphs. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2006, v:39, n:4, pp:539-551 [Journal]
  20. Miguel Cazorla, Francisco Escolano
    Two Bayesian methods for junction classification. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Image Processing, 2003, v:12, n:3, pp:317-327 [Journal]
  21. Wendy Aguilar, M. Elena Martínez-Pérez, Yann Frauel, Francisco Escolano, Miguel Angel Lozano, Arturo Espinosa-Romero
    Graph-Based Methods for Retinal Mosaicing and Vascular Characterization. [Citation Graph (0, 0)][DBLP]
    GbRPR, 2007, pp:25-36 [Conf]
  22. Boyan Bonev, Francisco Escolano, Miguel Angel Lozano, Pablo Suau, Miguel Cazorla, Wendy Aguilar
    Constellations and the Unsupervised Learning of Graphs. [Citation Graph (0, 0)][DBLP]
    GbRPR, 2007, pp:340-350 [Conf]
  23. Pablo Suau, Francisco Escolano
    Exploiting Information Theory for Filtering the Kadir Scale-Saliency Detector. [Citation Graph (0, 0)][DBLP]
    IbPRIA (2), 2007, pp:146-153 [Conf]
  24. Boyan Bonev, Francisco Escolano, Miguel Cazorla
    A Novel Information Theory Method for Filter Feature Selection. [Citation Graph (0, 0)][DBLP]
    MICAI, 2007, pp:431-440 [Conf]

  25. A New Feasible Approach to Multi-dimensional Scale Saliency. [Citation Graph (, )][DBLP]


  26. Flow Complexity: Fast Polytopal Graph Complexity and 3D Object Clustering. [Citation Graph (, )][DBLP]


  27. Birkhoff polytopes, heat kernels and graph complexity. [Citation Graph (, )][DBLP]


  28. Multi-dimensional Scale Saliency Feature Extraction Based on Entropic Graphs. [Citation Graph (, )][DBLP]


  29. Kernelization of Softassign and Motzkin-Strauss Algorithms. [Citation Graph (, )][DBLP]


  30. Polytopal Graph Complexity, Matrix Permanents, and Embedding. [Citation Graph (, )][DBLP]


  31. Entropy-Based Variational Scheme for Fast Bayes Learning of Gaussian Mixtures. [Citation Graph (, )][DBLP]


  32. High-Dimensional Spectral Feature Selection for 3D Object Recognition Based on Reeb Graphs. [Citation Graph (, )][DBLP]


  33. Analysis of the Multi-Dimensional Scale Saliency Algorithm and Its Application to Texture Categorization. [Citation Graph (, )][DBLP]


  34. What Is the Complexity of a Network? The Heat Flow-Thermodynamic Depth Approach. [Citation Graph (, )][DBLP]


  35. Ceiling mosaics through information-based SLAM. [Citation Graph (, )][DBLP]


  36. Contextual visual localization: cascaded submap classification, optimized saliency detection, and fast view matching. [Citation Graph (, )][DBLP]


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