Network Flow Formulations for Learning Binary Hashing

No abstract is available for this paper.

• Publication year

  2016

• Venue

  European Conference on Computer Vision

• Publication date

  2016-10-08

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1007/978-3-319-46454-1_23
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Inference

  2020cited by this paper
• An NMF Perspective on Binary Hashing

  2015cited by this paper
• Supervised Discrete Hashing

  2015cited by this paper
• Discrete Graph Hashing

  2014cited by this paper
• Two-Stage Hashing for Fast Document Retrieval

  2014cited by this paper
• Graph Cuts for Supervised Binary Coding

  2014cited by this paper
• A General Two-Step Approach to Learning-Based Hashing

  2013cited by this paper
• The Power of Asymmetry in Binary Hashing

  2013cited by this paper
• Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality

  2012cited by this paper
• Multidimensional Spectral Hashing

  2012cited by this paper
• Generalized roof duality for pseudo-boolean optimization

  2011cited by this paper
• Minimal Loss Hashing for Compact Binary Codes

  2011cited by this paper
• Scale invariant cosegmentation for image groups

  2011cited by this paper
• Hashing with Graphs

  2011cited by this paper
• Using very deep autoencoders for content-based image retrieval

  2011cited by this paper
• Iterative quantization: A procrustean approach to learning binary codes

  2011cited by this paper
• Self-taught hashing for fast similarity search

  2010cited by this paper
• Generalized roof duality and bisubmodular functions

  2010cited by this paper
• Minimizing sparse higher order energy functions of discrete variables

  2009cited by this paper
• Learning to Hash with Binary Reconstructive Embeddings

  2009cited by this paper
• Semantic hashing

  2009cited by this paper
• Half-integrality based algorithms for cosegmentation of images

  2009cited by this paper
• Kernelized locality-sensitive hashing for scalable image search

  2009cited by this paper
• Minimizing Nonsubmodular Functions with Graph Cuts-A Review

  2007cited by this paper
• Optimizing Binary MRFs via Extended Roof Duality

  2007cited by this paper
• Kernels as features: On kernels, margins, and low-dimensional mappings

  2006cited by this paper
• Size Regularized Cut for Data Clustering

  2005cited by this paper
• Fast pose estimation with parameter-sensitive hashing

  2003cited by this paper
• Pseudo-Boolean optimization

  2002cited by this paper
• A simple min-cut algorithm

  1997cited by this paper
• An Optimal Graph Theoretic Approach to Data Clustering: Theory and Its Application to Image Segmentation

  1993cited by this paper

• Learning to Learn for Small Sample Visual Recognition

  2018cites this paper
• Few-Shot Hash Learning for Image Retrieval

  2017cites this paper