Histogram Intersection Kernels
Histogram Intersection Kernels is a kernel function in machine learning that belongs to the family of positive definite kernels and is distinguished by measuring similarity between two histograms through the summation of the minima of their corresponding bin values, effectively quantifying overlap in histogram-based feature representations.
49
Publications
5.1K
Citations
137
Authors
60
Institutions
Publications per year
2017–2026
6
Parents
49
Histogram intersection kernel for image classification
Annalisa Barla, Francesca Odone, Alessandro Verri · 2004 · 280 citations
1–5 of 49
137
3
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 137
60

Peking University
Beijing, China
4 h-index
11 publications
162 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
6 publications
402 citations
Nanyang Technological University
Singapore, Singapore
3 h-index
5 publications
704 citations

Harbin Institute of Technology
Harbin, China
3 h-index
10 publications
276 citations

Sorbonne Université
Paris, France
2 h-index
5 publications
457 citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
2 h-index
7 publications
173 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
3 publications
124 citations

Beihang University
Beijing, China
2 h-index
3 publications
51 citations
1–8 of 60
3 publications · 381 citations
3
h-index
2 publications · 143 citations
2
h-index
1 publications · 10 citations
1
h-index
1 publications · 49 citations
1
h-index
1 publications · 15 citations
1
h-index
1–5