A Fast Implementation of the ISOCLUS Algorithm

Nargess Memarsadeghi; David M. Mount; Nathan S. Netanyahu; Jacqueline Le Moigne

A Fast Implementation of the ISOCLUS Algorithm

Nargess Memarsadeghi, David M. Mount, Nathan S. Netanyahu, Jacqueline Le Moigne

Department of Computer Science

Research output: Contribution to conference › Paper › peer-review

6 Scopus citations

Abstract

The efficiency of implementation of the ISOCLUS algorithms was analyzed. The analysis was based on the use of kd-tree data structure and filtering algorithms. The speed-ups in running times on synthetic clustered data and landsat image data ranged from 10 to 30 and 3 to 6 respectively.

Original language	English
Pages	2057-2059
Number of pages	3
State	Published - 2003
Event	2003 IGARSS: Learning From Earth's Shapes and Colours - Toulouse, France Duration: 21 Jul 2003 → 25 Jul 2003

Conference

Conference	2003 IGARSS: Learning From Earth's Shapes and Colours
Country/Territory	France
City	Toulouse
Period	21/07/03 → 25/07/03

Cite this

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title = "A Fast Implementation of the ISOCLUS Algorithm",

abstract = "The efficiency of implementation of the ISOCLUS algorithms was analyzed. The analysis was based on the use of kd-tree data structure and filtering algorithms. The speed-ups in running times on synthetic clustered data and landsat image data ranged from 10 to 30 and 3 to 6 respectively.",

author = "Nargess Memarsadeghi and Mount, {David M.} and Netanyahu, {Nathan S.} and {Le Moigne}, Jacqueline",

year = "2003",

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T1 - A Fast Implementation of the ISOCLUS Algorithm

AU - Memarsadeghi, Nargess

AU - Mount, David M.

AU - Netanyahu, Nathan S.

AU - Le Moigne, Jacqueline

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Y1 - 2003

N2 - The efficiency of implementation of the ISOCLUS algorithms was analyzed. The analysis was based on the use of kd-tree data structure and filtering algorithms. The speed-ups in running times on synthetic clustered data and landsat image data ranged from 10 to 30 and 3 to 6 respectively.

AB - The efficiency of implementation of the ISOCLUS algorithms was analyzed. The analysis was based on the use of kd-tree data structure and filtering algorithms. The speed-ups in running times on synthetic clustered data and landsat image data ranged from 10 to 30 and 3 to 6 respectively.

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AN - SCOPUS:0242710786

SP - 2057

EP - 2059

T2 - 2003 IGARSS: Learning From Earth's Shapes and Colours

Y2 - 21 July 2003 through 25 July 2003

ER -

A Fast Implementation of the ISOCLUS Algorithm

Abstract

Conference

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