文献
J-GLOBAL ID:202002227400527265
整理番号:20A0571860
CBIRのための関連フィードバックを用いたSURF-COHOGベースのスパース特徴を用いたBOVWモデルの性能のブースティング【JST・京大機械翻訳】
Boosting the Performance of the BoVW Model Using SURF-CoHOG-Based Sparse Features with Relevance Feedback for CBIR
著者 (7件):
Baig Fahad
(Department of Software Engineering, University of Engineering and Technology, Taxila, Pakistan)
,
Mehmood Zahid
(Department of Software Engineering, University of Engineering and Technology, Taxila, Pakistan)
,
Rashid Muhammad
(Department of Computer Engineering, Umm Al-Qura University, Mecca, Saudi Arabia)
,
Javid Muhammad Arshad
(Department of Basic Sciences, University of Engineering and Technology, Taxila, Pakistan)
,
Rehman Amjad
(College of Computer and Information Systems, Al-Yamamah University, Riyadh, Saudi Arabia)
,
Saba Tanzila
(College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia)
,
Adnan Ahmed
(Department of Computer Sciences, University of Engineering and Technology, Taxila, Pakistan)
資料名:
Iranian Journal of Science and Technology, Transactions of Electrical Engineering
(Iranian Journal of Science and Technology, Transactions of Electrical Engineering)
巻:
44
号:
1
ページ:
99-118
発行年:
2020年
JST資料番号:
W4504A
ISSN:
2228-6179
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)