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for(i = 1; i LTE 10; i = i + 1) { if(RandRange(1,10) EQ 10) { continue; } WriteOutput( #i#<br> ); }

weight the results according to the natural class distribution. All the results are reported at 0% rejection rate, with the exception of the approaches based on FingerCode feature vectors (Jain et al. [83], Marcialis et al. [80], Yao et al. [82], Yao et al. [84]), where 1.8% ngerprints are discarded during the feature extraction stage.

E[F ] with model error = E[F ] w/o model error 1.05 V [e] = (0.07 increased E[F ])2

In this example, whenever ColdFusion calculates a random value equal to 10, it skips the WriteOutput() statement and instead skips to the beginning of the next iteration of the loop, if any iterations remain.

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In this chapter the main learning-based approaches to ngerprint acquisition, processing, recognition, and classi cation have been discussed. It is not surprising that tasks where the application of learning seems to provide maximum bene t are those that are critical for humans (e.g., quality check, liveness detection, continuous and exclusive classi cation, etc.). Combination of classi ers (both at feature and at score level) and automatic selection of redundant features proved to be very effective to improve the accuracy of ngerprint veri cation; SVM and other robust classi cation techniques were successfully applied to ngerprint veri cation formulated as a two class problem. The two main factors limiting the performance of learning based techniques are still the availability of reliable large-enough training data set and the lack of ef ciency of some techniques such as the exhaustive classi cation of small portions of the image to detect minutiae. The authors believe that important advances could arise by the availability of large sets of ad hoc-created synthetic ngerprints [90] and the implementation of boosted cascade of weak classi ers (such as in reference 3) that allows us to solve in real time and with good accuracy the face detection problem.

You cannot use CFML comments within a CFSCRIPT block. Instead, you must use one of the CFSCRIPT comment types, as follows:

<cfscript> // This is a single-line comment before some code. myVar = 1;

The authors want to thank F. Roli, G. Marcialis, and P. Coli for sharing the vitality data set used in this chapter.

Single-line comments begin with two forward slashes the entire line after the slash marks is commented out, meaning that any code in that line does not execute. Multiline comments are surrounded by /* and */ everything in between those two marks is a comment. You cannot nest multiline comments inside one another, but you can nest a single-line comment inside a multiline comment.

0 friction density D crust D till Parameter cu (M) cu (L)

CFSCRIPT has the following two primary advantages: It is often more understandable to use CFSCRIPT than CFML in processing data, because CFSCRIPT s procedural syntax is often clearer than that of CFML. You get a healthy performance gain form using CFSCRIPT. CFML is basically an XMLbased language and, as such, must be parsed by an XML parser and executed by an interpreter, and both operations are relatively slow. CFSCRIPT requires only a single XML-based tag pair to be parsed, after which its contents essentially a simple list of preparsed commands are passed to the processing engine all at once. Sometimes entire pages of code are written in CFSCRIPT. The best practice is to analyze your templates to determine whether you can group together large blocks of code that don t require CFML tags and then write that code as a single CFSCRIPT block. Sometimes you must interweave CFSCRIPT blocks with CFML, in which case you should try to minimize the number of CFSCRIPT blocks that you create in a single template.

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