H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 37 Citations 5,877 205 World Ranking 5316 National Ranking 38

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Statistics

His main research concerns Cluster analysis, Artificial intelligence, Algorithm, Pattern recognition and Correlation clustering. His studies in Cluster analysis integrate themes in fields like Data mining and Explained sum of squares. His study looks at the relationship between Artificial intelligence and topics such as Computer vision, which overlap with Identification.

His study in the fields of Time complexity, Cultural algorithm and Approximation algorithm under the domain of Algorithm overlaps with other disciplines such as Simple. As a part of the same scientific family, Pasi Fränti mostly works in the field of Pattern recognition, focusing on Normalization and, on occasion, Feature vector, Speaker recognition, Mixture model and Speaker diarisation. His Single-linkage clustering research incorporates themes from Determining the number of clusters in a data set and Nearest-neighbor chain algorithm.

His most cited work include:

  • Real-time speaker identification and verification (213 citations)
  • Iterative shrinking method for clustering problems (205 citations)
  • Outlier detection using k-nearest neighbour graph (205 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Artificial intelligence, Pattern recognition, Algorithm, Cluster analysis and Computer vision. His Artificial intelligence study which covers Speech recognition that intersects with Feature extraction. His Pattern recognition research is multidisciplinary, relying on both Nearest neighbour algorithm and Gaussian noise.

In his study, Nearest-neighbor chain algorithm is strongly linked to k-nearest neighbors algorithm, which falls under the umbrella field of Algorithm. Correlation clustering, CURE data clustering algorithm, Canopy clustering algorithm, Fuzzy clustering and k-medians clustering are among the areas of Cluster analysis where the researcher is concentrating his efforts. His studies deal with areas such as Codebook and Centroid as well as Vector quantization.

He most often published in these fields:

  • Artificial intelligence (53.11%)
  • Pattern recognition (31.95%)
  • Algorithm (28.22%)

What were the highlights of his more recent work (between 2017-2021)?

  • Cluster analysis (26.97%)
  • Algorithm (28.22%)
  • Artificial intelligence (53.11%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Cluster analysis, Algorithm, Artificial intelligence, Global Positioning System and Pattern recognition. The concepts of his Cluster analysis study are interwoven with issues in Measure, Point, Data mining and Iterated function. Pasi Fränti has included themes like Graph, k-means clustering, Motion planning and Curse of dimensionality in his Algorithm study.

His Artificial intelligence study frequently draws connections between related disciplines such as Series. His research in Global Positioning System intersects with topics in Object detection, Information retrieval, Search engine indexing and Computer vision. His Pattern recognition research includes themes of Object and Divergence.

Between 2017 and 2021, his most popular works were:

  • K-means properties on six clustering benchmark datasets (121 citations)
  • How much can k-means be improved by using better initialization and repeats? (74 citations)
  • Efficiency of random swap clustering (22 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Algorithm
  • Statistics

Pasi Fränti mainly investigates Algorithm, Cluster analysis, Artificial intelligence, Pattern recognition and Global Positioning System. His Algorithm study combines topics in areas such as Graph, Metric, k-means clustering, Graph and Benchmark. As part of one scientific family, Pasi Fränti deals mainly with the area of Cluster analysis, narrowing it down to issues related to the Time complexity, and often Iterated function and Expected value.

His study connects Natural language processing and Artificial intelligence. The study incorporates disciplines such as Entropy and Median absolute deviation in addition to Pattern recognition. His Global Positioning System research integrates issues from Grid and Data mining.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Outlier detection using k-nearest neighbour graph

V. Hautamaki;I. Karkkainen;P. Franti.
international conference on pattern recognition (2004)

464 Citations

Iterative shrinking method for clustering problems

Pasi Fränti;Olli Virmajoki.
Pattern Recognition (2006)

296 Citations

Real-time speaker identification and verification

T. Kinnunen;E. Karpov;P. Franti.
IEEE Transactions on Audio, Speech, and Language Processing (2006)

284 Citations

Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph

P. Franti;O. Virmajoki;V. Hautamaki.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

276 Citations

Compression of Digital Images by Block Truncation Coding: A Survey

Pasi Fränti;Olli Nevalainen;Timo Kaukoranta.
The Computer Journal (1994)

176 Citations

Randomised Local Search Algorithm for the Clustering Problem

Pasi Fränti;Juha Kivijärvi.
Pattern Analysis and Applications (2000)

167 Citations

K-means properties on six clustering benchmark datasets

Pasi Fränti;Sami Sieranoja.
Applied Intelligence (2018)

161 Citations

Eye-Movements as a biometric

Roman Bednarik;Tomi Kinnunen;Andrei Mihaila;Pasi Fränti.
scandinavian conference on image analysis (2005)

158 Citations

Genetic Algorithms for Large-Scale Clustering Problems

Pasi Fränti;Juha Kivijärvi;Timo Kaukoranta;Olli Nevalainen.
The Computer Journal (1997)

136 Citations

Improving k-means by outlier removal

Ville Hautamäki;Svetlana Cherednichenko;Ismo Kärkkäinen;Tomi Kinnunen.
scandinavian conference on image analysis (2005)

136 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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