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231223s2005 xx ||||| 00| ||eng c |
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|a eng
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| 100 |
1 |
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|a Merryman, Thomas E
|e verfasserin
|4 aut
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| 245 |
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|a An adaptive multirate algorithm for acquisition of fluorescence microscopy data sets
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|c 2005
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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|a Date Completed 27.10.2005
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|a Date Revised 10.12.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a We propose an algorithm for adaptive efficient acquisition of fluorescence microscopy data sets using a multirate (MR) approach. We simulate acquisition as part of a larger system for protein classification based on their subcellular location patterns and, thus, strive to maintain the achieved level of classification accuracy as much as possible. This problem is similar to image compression but unique due to additional restrictions, namely causality; we have access only to the information scanned up to that point. While we do want to acquire fewer samples with as low distortion as possible to achieve compression, our goal is to do so while affecting the overall classification accuracy as little as possible. We achieve this by using an adaptive MR scanning scheme which samples the regions of the image area that hold the most pertinent information. Our results show that we can achieve significant compression which we can then use to aquire faster or to increase space resolution of our data set, all while minimally affecting the classification accuracy of the entire system
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|a Comparative Study
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|a Evaluation Study
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 700 |
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|a Kovacević, Jelena
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 14(2005), 9 vom: 01. Sept., Seite 1246-53
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|x 1941-0042
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|g volume:14
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|g pages:1246-53
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