For Hyperspectral image (HSI) datasets, each class have their salient feature and classifiers classify HSI datasets according to the class's saliency features, however, there will be different salient features when use different normalization method. In this letter, we report the effect on classifiers by different normalization methods and recommend the best normalization methods for classifier...

Van Raan et al. (2010; arXiv:1003.2113) have proposed a new indicator (MNCS) for field normalization. Since field normalization is also used in the Leiden Rankings of universities, we elaborate our critique of journal normalization in Opthof & Leydesdorff (2010; arXiv:1002.2769) in this rejoinder concerning field normalization. Fractional citation counting thoroughly solves the issue of normali...

The work presented in this paper deals with the text normalization for highly inflectional languages. This paper is focused on abbreviation expansion and likewise on numerals normalization. Our text normalization system does not use any explicit parser or part-of-speech tagger and thus it can be called lightly supervised. The standard rule-based text normalization method is compared with the pr...

近幾十年來,無數的學者先進對於此雜訊干擾問題提出了豐富眾多的演算法,略分成兩 大類別:強健性語音特徵參數表示法(robust speech feature representation)與語音模型調適 法(speech model adaptation),第一類別之方法主要目的在抽取不易受到外在環境干擾下 而失真的語音特徵參數,或從原始語音特徵中儘量削減雜訊造成的效應,比較知名的方 法有:倒頻譜平均值與變異數正規化法 (cepstral mean and variance normalization, CMVN)[1]、倒頻譜統計圖正規化法(cepstral histogram normalization, CHN)[2]、倒頻譜平 均值與變異數正規化結合自動回歸動態平均濾波器法(cepstral mean and variance normalization plus auto-r...

Malware is code designed for a malicious purpose, such as obtaining root privilege on a host. A malware detector identifies malware and thus prevents it from adversely affecting a host. In order to evade detection by malware detectors, malware writers use various obfuscation techniques to transform their malware. There is strong evidence that commercial malware detectors are susceptible to thes...

Previous photos and videos This work explores normalization for parser adaptation. Traditionally, normalization is used as separate preprocessing step. We show that integrating the normalization model into the parsing algorithm is beneficial. To this end, we use a normalization model combined with the parsing as intersection algorithm. This way, multiple normalization candidates can be leverage...