Vector Distance Metrics is a mathematical framework that quantifies the dissimilarity between two vectors in a vector space by leveraging specific geometric or statistical measures such as Euclidean, Manhattan, or cosine distance.
65
Publications
4.8K
Citations
140
Authors
68
Institutions
Publications per year
2017–2026
11
Variants
Vector Distance Measures
Parents
Publications
65
J. R. Retherford · Bulletin of the American Mathematical Society · 1978 · 657 citations · Full text
Distance measures for signal processing and pattern recognition
Michèle Basseville · Signal Processing · 1989 · 618 citations · Full text
1–5 of 65
Authors
140
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1–5 of 140
Institutions
68
University of Toronto
Toronto, Canada
4 h-index
7 publications
494 citations
Mallinckrodt (United States)
Hazelwood, United States
3 h-index
10 publications
324 citations
Radboud University Nijmegen
Nijmegen, The Netherlands
2 h-index
3 publications
74 citations
Toronto Metropolitan University
Toronto, Canada
2 h-index
2 publications
137 citations
Stockholm University
Stockholm, Sweden
2 h-index
3 publications
74 citations
University of Udine
Udine, Italy
1 h-index
3 publications
141 citations
Edinburgh Napier University
Edinburgh, United Kingdom
1 h-index
4 publications
244 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
1 h-index
2 publications
60 citations
1–8 of 68
Venues
- Pattern Recognition
2 publications · 98 citations
2
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- Computer Aided Surgery
CAS · 2 publications · 30 citations
2
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- Acta Psychologica
2 publications · 62 citations
2
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- Pacific Journal of Mathematics
2 publications · 207 citations
2
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- Proceedings of the AAAI Conference on Artificial Intelligence
Conference · 1 publications · 40 citations
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1–5