Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Fisher kernel

In statistical classification, the Fisher kernel, named after Ronald Fisher, is a function that measures the similarity of two objects on the basis… Expand
Wikipedia

Related topics

Related topics

9 relations
Fisher informationGenerative modelHidden Markov modelKernel method
Expand

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams
Algebraic topology methods have recently played an important role for statistical analysis with complicated geometric structured… Expand
  • figure 1
  • table 1
  • table 3
  • table 2
  • figure 2
Highly Cited
2014
Highly Cited
2014
Deep Fisher Kernels -- End to End Learning of the Fisher Kernel GMM Parameters
Fisher Kernels and Deep Learning were two developments with significant impact on large-scale object categorization in the last… Expand
  • table 1
  • table 2
  • table 3
Highly Cited
2014
Highly Cited
2014
Triangulation Embedding and Democratic Aggregation for Image Search
We consider the design of a single vector representation for an image that embeds and aggregates a set of local patch descriptors… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Highly Cited
2013
Highly Cited
2013
Image Classification with the Fisher Vector: Theory and Practice
A standard approach to describe an image for classification and retrieval purposes is to extract a set of local patch descriptors… Expand
  • figure 1
  • table 1
  • figure 2
  • table 2
  • figure 3
Highly Cited
2011
Highly Cited
2011
Learning Discriminative Fisher Kernels
Fisher kernels provide a commonly used vectorial representation of structured objects. The paper presents a technique that… Expand
  • table 1
  • table 3
  • table 2
  • table 4
Highly Cited
2010
Highly Cited
2010
Improving the Fisher Kernel for Large-Scale Image Classification
The Fisher kernel (FK) is a generic framework which combines the benefits of generative and discriminative approaches. In the… Expand
  • figure 1
  • table 1
  • table 2
  • table 3
  • table 4
Highly Cited
2010
Highly Cited
2010
Large-scale image retrieval with compressed Fisher vectors
The problem of large-scale image search has been traditionally addressed with the bag-of-visual-words (BOV). In this article, we… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 5
  • figure 4
Highly Cited
2007
Highly Cited
2007
Fisher Kernels on Visual Vocabularies for Image Categorization
Within the field of pattern classification, the Fisher kernel is a powerful framework which combines the strengths of generative… Expand
  • figure 1
  • figure 2
  • table 1
  • table 2
  • figure 3
Highly Cited
2003
Highly Cited
2003
A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications
Over the last years significant efforts have been made to develop kernels that can be applied to sequence data such as DNA, text… Expand
  • table 1
  • table 2
  • table 3
  • figure 1
Highly Cited
2002
Highly Cited
2002
Mismatch String Kernels for SVM Protein Classification
We introduce a class of string kernels, called mismatch kernels, for use with support vector machines (SVMs) in a discriminative… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License
ACCEPT & CONTINUE