尾上研究室 研究業績一覧: E. Aliwarga, J. Yu, M. Hatanaka, and T. Onoye, Hardware Architecture of Generic Soft Cascaded Linear Svm Classifier, June 2015.
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E. Aliwarga, J. Yu, M. Hatanaka, and T. Onoye, "Hardware Architecture of Generic Soft Cascaded Linear Svm Classifier," 75, 電子情報通信学会ディペンダブルコンピューティング研究会, June 2015.
ID 824
分類 研究会等発表論文
タグ
表題 (title) Hardware Architecture of Generic Soft Cascaded Linear Svm Classifier
表題 (英文) Hardware Architecture of Generic Soft Cascaded Linear Svm Classifier
著者名 (author) E. Aliwarga,J. Yu,M. Hatanaka,T. Onoye
英文著者名 (author)
キー (key) Eric Aliwarga,Jaehoon Yu , Masahide Hatanaka, Takao Onoye
号数 (number) 75
技術報告書の種別 (type)
発行元組織 (organization) 電子情報通信学会ディペンダブルコンピューティング研究会
出版社住所 (address)
刊行月 (month) 6
出版年 (year) 2015
URL
付加情報 (note)
注釈 (annote)
内容梗概 (abstract) Support Vector Machine is renowned as a powerful machine learning algorithm for many classi cation problems. However, among all the works proposed for SVM hardware implementation, a lot of them are designed solely for speci c purpose. This paper presents an SVM hardware architecture capable of classifying input data with arbitrary vector dimensionality and arbitrary precision, resulting in a generic support vector machine capable of classifying various targets. The proposed architecture also employs a speed-up method called soft cascade algorithm to enhance its performance. The results show that for CoHOG pedestrian detection, the proposed hardware architecture may classify up to 77 VGA images per second even under the condition that the architecture is not designed speci cally for the mentioned purpose.
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BiBTeXエントリ
@techreport{id824,
         title = {Hardware Architecture of Generic Soft Cascaded Linear SVM Classifier},
        author = {E. Aliwarga and J. Yu and M. Hatanaka and T. Onoye},
        number = {75},
    institution = {電子情報通信学会ディペンダブルコンピューティング研究会},
         month = {6},
          year = {2015},
}
  

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