A Novel Active Learning Method in Relevance Feedback for Content-Based Remote Sensing Image Retrieval

IEEE Transactions on Geoscience and Remote Sensing - Tập 53 Số 5 - Trang 2323-2334 - 2015
Begüm Demir1, Lorenzo Bruzzone1
1Department of Information Engineering and Computer Science, University of Trento, Trento, Italy

Tóm tắt

Từ khóa


Tài liệu tham khảo

10.1109/TGRS.2007.892007

10.1109/IGARSS.2004.1370126

10.1109/ICOSP.2004.1452767

10.1109/34.531803

10.1364/AO.43.000210

10.1016/j.patcog.2009.01.035

newsam, 0, Retrieval using texture features in high resolution multi-spectral satellite imagery, Proc SPIE Defense Security Symp Data Mining Knowl Discov Theory Tools Technology VI, 21

10.1109/TGRS.2012.2205158

bruzzone, 2012, Active learning methods in classification of remote sensing images, Signal and Image Processing for Remote sensing, 303

schohn, 0, Less is more: Active learning with support vector machines, Proc 17th Int Conf Mach Learn, 839

10.1007/s00530-002-0070-3

wu, 0, A fast dual method for HIK SVM learning, Proc 11th Eur Conf Comput Vis, 552

hong, 0, Incorporate support vector machines to content-based image retrieval with relevant feedback, Proc IEEE Int Conf Image Process, 750, 10.1109/ICIP.2000.899563

10.1109/IGARSS.2002.1026510

bao, 0, Comparative studies on similarity measures for remote sensing image retrieval, Proc IEEE Int Conf Syst Man Cybern, 1112

10.1109/TGRS.2010.2088404

bretschneider, 0, A retrieval system for remotely sensed imagery, Proc Int Conf Imag Sci Syst Technol, 439

10.1145/1348246.1348248

ma, 0, Local shape association based retrieval of infrared satellite images, Proc IEEE Int Symp Multimedia, 551

10.1109/34.895972

tong, 2001, Support vector machine active learning with applications to text classification, J Mach Learn Res, 2, 45

zhang, 0, A large scale clustering scheme for kernel k-means, Proc IEEE Int Conf Pattern Recog, 289

brinker, 0, Incorporating diversity in active learning with support vector machines, Proc Int Conf Mach Learn, 59

10.1017/CBO9780511809071

10.1162/089976698300017467

10.1109/CVPR.2008.4587630

10.1109/ICIP.2003.1247294