Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
Improved Stratified Sampling Using Dart Throwing |
ÀúÀÚ(Author) |
ÇÏÀç°æ
Ȳº¸È¿Á¤
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ÀåÁöÇö
Jaekyung Ha
Hyojeong Hwangbo
Hyojeong Gwon
Jihyun Jang
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À±´ÙÀº
±è¿¬¼ö
À±ÇöÁø
Suhan Bae
Daeun Yun
Yeonsu Kim
Hyunjin Yun
ÀÌ¿¹ÀÎ
±è¿µ±¸
¾È¹Î±Ô
Yein Lee
Young Goo Kim
Minkyu Ahn
°íÁöÀº
À̼º±æ
Jieun Ko
Sungkil Lee
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¿ø¹®¼ö·Ïó(Citation) |
VOL 48 NO. 05 PP. 0527 ~ 0532 (2021. 05) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
This paper presents a stratified sampling technique in which sampling areas are chosen through the dart-throwing technique. Stochastic sampling techniques, which are used in various fields such as image processing and computer graphics, produce images of high quality as samples distribute uniformly and randomly. The blue-noise pattern removes low-frequency areas that are critical in the aliasing problem, but computing such a pattern is costly. To address this issue, stratified sampling methods have been proposed; however, the method demonstrates low randomness due to the structure. This paper proposes a technique to increase randomness by determining the sampling area in the stratified structure through the dart-throwing technique. Our method randomly samples areas in which samples are jittered.
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Å°¿öµå(Keyword) |
ÆÄŲ½¼º´
º»Å¼º ÁøÀü
ÀÌ»ó¿îµ¿Áõ
¿ÀÇ ¼Ò½º
ÅÂºí¸´ PC
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essential tremor
movement disorder
open source
tablet PC
healthcare
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stochastic sampling
stratified sampling
anti-aliasing
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