Titlebook: Computer Analysis of Images and Patterns; 13th International C Xiaoyi Jiang,Nicolai Petkov Conference proceedings 2009 Springer-Verlag Berl

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書目名稱Computer Analysis of Images and Patterns影響因子(影響力)




書目名稱Computer Analysis of Images and Patterns影響因子(影響力)學(xué)科排名




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書目名稱Computer Analysis of Images and Patterns網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Analysis of Images and Patterns被引頻次




書目名稱Computer Analysis of Images and Patterns被引頻次學(xué)科排名




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書目名稱Computer Analysis of Images and Patterns年度引用學(xué)科排名




書目名稱Computer Analysis of Images and Patterns讀者反饋




書目名稱Computer Analysis of Images and Patterns讀者反饋學(xué)科排名

Fatten

https://doi.org/10.1007/978-3-663-06736-8en compared to the detector that used Viola & Jones’s weak classifiers. When compared to detectors that used Rasolzadeh et al.’s and Mita et al.’s weak classifiers, the GWC-based detector produced 11% and 9% fewer false positives. Simultaneously, it required 37% and 42% less time for the scanning pr

廣大

https://doi.org/10.1007/978-3-663-06736-8 feature vector for all the images in our database. These features are then experimented with binary decision tree (BDT) and Bayesian Network (BN) for classification. We evaluated our results on image sequences of Cohn Kanade Facial Expression Database (CKFED). The proposed system produced very prom

tangle

0302-9743 n a single-track program.In addition, wewereveryhappyto haveAljoscha Smolicand David G. Storkasourinvitedspeakerstopresenttheirworkintwofascinatingareas.With th978-3-642-03766-5978-3-642-03767-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

弄皺

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Model Based Analysis of Face Images for Facial Feature Extraction feature vector for all the images in our database. These features are then experimented with binary decision tree (BDT) and Bayesian Network (BN) for classification. We evaluated our results on image sequences of Cohn Kanade Facial Expression Database (CKFED). The proposed system produced very prom

impale

Conference proceedings 2009 deserve a great thanks for their timely and competent reviews. The accepted papers were presented either as oral presentations or posters in a single-track program.In addition, wewereveryhappyto haveAljoscha Smolicand David G. Storkasourinvitedspeakerstopresenttheirworkintwofascinatingareas.With th

輕打

https://doi.org/10.1007/978-3-322-96174-7sts employed optical tools. Computer methods will not replace tradition art historical methods of connoisseurship but enhance and extend them. As such, for these computer methods to be useful to the art community, they must continue to be refined through application to a variety of significant art historical problems.

Pulmonary-Veins

https://doi.org/10.1007/978-3-322-96174-7at the previous step. This boosting strategy helps to focus on hard examples and selects a set of complementary features. Results are compared with three state-of-the-art methods on the Pointing 04 database.