Titlebook: Biometric Authentication; ECCV 2004 Internatio Davide Maltoni,Anil K. Jain Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 20

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書目名稱Biometric Authentication影響因子(影響力)




書目名稱Biometric Authentication影響因子(影響力)學科排名




書目名稱Biometric Authentication網(wǎng)絡公開度




書目名稱Biometric Authentication網(wǎng)絡公開度學科排名




書目名稱Biometric Authentication被引頻次




書目名稱Biometric Authentication被引頻次學科排名




書目名稱Biometric Authentication年度引用




書目名稱Biometric Authentication年度引用學科排名




書目名稱Biometric Authentication讀者反饋




書目名稱Biometric Authentication讀者反饋學科排名

引起

狂亂

Biometric Face Authentication Using Pixel-Based Weak Classifiersscale face image into a Linear Discriminant subspace as input of a classifier such as Support Vector Machines or Multi-layer Perceptrons. Unfortunately, these classifiers involve thousands of parameters that are difficult to store on a smart-card for instance. Recently, boosting algorithms has emerg

coddle

Null Space Approach of Fisher Discriminant Analysis for Face Recognitionll space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysis, we present the NLDA algorithm and the most suitable situation for NLDA. Our method is simpler than all other null space appr

注意

翅膀拍動

Towards a Robust Face Detectorith image-based analysis, in order to better exploit the main characteristics available in the input image. Different modules contribute to the face detection task: 1) a template-based approach initially proposed in [12], 2) an edge-extraction technique well suited to deal with illumination-changes,

Neuralgia

A簡潔的

reject

Benchmarking of Fingerprint Sensorshodology is available. This paper attempts to address this deficiency by proposing a new methodology to benchmark the fingerprint sensors. The methodology consists of three metrics and the associated procedures to collect the data in order to compute the proposed metrics. Two small scale experiments

魅力

Detecting Liveness in Fingerprint Scanners Using Wavelets: Results of the Test Datasetve people, is used as a measure to classify ‘live’ fingers from ‘not live’ fingers. Pre-processing involves filtering of the images using different image processing techniques. Wavelet analysis of the images is performed using Daubechies wavelet. Multiresolution analysis is performed to extract info