Using human computation in dead-zone based 2D pattern matching

L.G.W.A. Cleophas; B.W. Watson; K. Awid

Using human computation in dead-zone based 2D pattern matching

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

50 Downloads (Pure)

Abstract

This paper examines the application of human computation (HC) to two-dimensional image pattern matching. The two main goals of our algorithm are to use turks as the processing units to perform an efficient pattern match attempt on a subsection of an image, and to divide the work using a version of dead-zone based pattern matching. In this approach, human computation presents an alternative to machine learning by outsourcing computationally difficult work to humans, while the dead-zone search offers an efficient search paradigm open to parallelization—making the combination a powerful approach for searching for patterns in two-dimensional images.

Original language	English
Title of host publication	Proceedings of the Prague Stringology Conference 2016, August 29-31, 2016, Prague, Czech Republic
Place of Publication	s.l.
Publisher	s.n.
Pages	22-32
Number of pages	11
ISBN (Print)	978-80-01-05996-8
Publication status	Published - 2016
Event	Prague Stringology Conference 2016 - Prague, Czech Republic Duration: 29 Aug 2016 → 31 Aug 2016

Conference

Conference	Prague Stringology Conference 2016
Country/Territory	Czech Republic
City	Prague
Period	29/08/16 → 31/08/16

Access to Document

publishers versionFinal published version, 414 KB

http://stringology.org/cgi-bin/getfile.cgi?t=pdf&c=-&y=2016&n=03

Cite this

@inproceedings{3320ea24f50a486a9e958d86d6be0ccc,

title = "Using human computation in dead-zone based 2D pattern matching",

abstract = "This paper examines the application of human computation (HC) to two-dimensional image pattern matching. The two main goals of our algorithm are to use turks as the processing units to perform an efficient pattern match attempt on a subsection of an image, and to divide the work using a version of dead-zone based pattern matching. In this approach, human computation presents an alternative to machine learning by outsourcing computationally difficult work to humans, while the dead-zone search offers an efficient search paradigm open to parallelization—making the combination a powerful approach for searching for patterns in two-dimensional images.",

author = "L.G.W.A. Cleophas and B.W. Watson and K. Awid",

year = "2016",

language = "English",

isbn = "978-80-01-05996-8",

pages = "22--32",

booktitle = "Proceedings of the Prague Stringology Conference 2016, August 29-31, 2016, Prague, Czech Republic",

publisher = "s.n.",

note = "Prague Stringology Conference 2016 ; Conference date: 29-08-2016 Through 31-08-2016",

}

TY - GEN

T1 - Using human computation in dead-zone based 2D pattern matching

AU - Cleophas, L.G.W.A.

AU - Watson, B.W.

AU - Awid, K.

PY - 2016

Y1 - 2016

N2 - This paper examines the application of human computation (HC) to two-dimensional image pattern matching. The two main goals of our algorithm are to use turks as the processing units to perform an efficient pattern match attempt on a subsection of an image, and to divide the work using a version of dead-zone based pattern matching. In this approach, human computation presents an alternative to machine learning by outsourcing computationally difficult work to humans, while the dead-zone search offers an efficient search paradigm open to parallelization—making the combination a powerful approach for searching for patterns in two-dimensional images.

AB - This paper examines the application of human computation (HC) to two-dimensional image pattern matching. The two main goals of our algorithm are to use turks as the processing units to perform an efficient pattern match attempt on a subsection of an image, and to divide the work using a version of dead-zone based pattern matching. In this approach, human computation presents an alternative to machine learning by outsourcing computationally difficult work to humans, while the dead-zone search offers an efficient search paradigm open to parallelization—making the combination a powerful approach for searching for patterns in two-dimensional images.

UR - http://stringology.org/event/2016/p03.html

M3 - Conference contribution

SN - 978-80-01-05996-8

SP - 22

EP - 32

BT - Proceedings of the Prague Stringology Conference 2016, August 29-31, 2016, Prague, Czech Republic

PB - s.n.

CY - s.l.

T2 - Prague Stringology Conference 2016

Y2 - 29 August 2016 through 31 August 2016

ER -

Using human computation in dead-zone based 2D pattern matching

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this