Titlebook: Structural, Syntactic, and Statistical Pattern Recognition; Joint IAPR Internati Adam Krzyzak,Ching Y. Suen,Nicola Nobile Conference procee

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書目名稱Structural, Syntactic, and Statistical Pattern Recognition影響因子(影響力)




書目名稱Structural, Syntactic, and Statistical Pattern Recognition影響因子(影響力)學(xué)科排名




書目名稱Structural, Syntactic, and Statistical Pattern Recognition網(wǎng)絡(luò)公開度




書目名稱Structural, Syntactic, and Statistical Pattern Recognition網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Structural, Syntactic, and Statistical Pattern Recognition被引頻次




書目名稱Structural, Syntactic, and Statistical Pattern Recognition被引頻次學(xué)科排名




書目名稱Structural, Syntactic, and Statistical Pattern Recognition年度引用




書目名稱Structural, Syntactic, and Statistical Pattern Recognition年度引用學(xué)科排名




書目名稱Structural, Syntactic, and Statistical Pattern Recognition讀者反饋




書目名稱Structural, Syntactic, and Statistical Pattern Recognition讀者反饋學(xué)科排名

lactic

能得到

,Annotation-Free Keyword Spotting in?Historical Vietnamese Manuscripts Using Graph Matching,orical Vietnamese manuscripts containing 719 scanned pages of the famous Tale of Kieu. Our results show that search terms can be found with promising precision both when providing handwritten samples (query by example) as well as printed characters (query by string).

MURKY

同步左右

Spatio-Temporal United Memory for Video Anomaly Detection,e AUC 96.92%, 87.43%, and 75.42% on UCSD Ped2, Avenue, and ShanghaiTech, respectively. Extensive experiments on three publicly available datasets demonstrate the excellent generalization and high effectiveness of the proposed method.

asthma

Self-supervised Out-of-Distribution Detection with Dynamic Latent Scale GAN,ual information of in-distribution data, and additional hyperparameters for prediction. The proposed method showed better out-of-distribution detection performance than the previous state-of-art method.

acrimony

知識

功多汁水

,Monte Carlo Dropout for?Uncertainty Analysis and?ECG Trace Image Classification,rld scenarios. We use ECG images dataset of cardiac and covid-19 patients containing five categories of data, which includes COVID-19 ECG records as well as data from other cardiovascular disorders. Our proposed model achieves 93.90% accuracy using this dataset.

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