Integrating active learning and crowdsourcing into large-scale supervised landcover mapping algorithms
作者： Stephanie R Debats , Lyndon D Estes , David R Thompson , Kelly K Caylor
DOI: 10.7287/PEERJ.PREPRINTS.3004V1
关键词:
摘要: … for the active learning query function to interact with crowdsourcing workers. Finally, 93 we present the results of a case study of agricultural field digitization in high-resolution, 94 multi-…
peerj.com
sci-hub.st 参考文章(16)
Alexander Liu, Joydeep Ghosh, Goo Jun, Spatially cost-sensitive active learning siam international conference on data mining. pp. 810- 821 ,(2009)
Robert Tibshirani, Trevor Hastie, Jerome H. Friedman, The Elements of Statistical Learning ,(2001)
Klaus Brinker, Incorporating diversity in active learning with support vector machines international conference on machine learning. pp. 59- 66 ,(2003)
Linda See, Ian McCallum, Steffen Fritz, Christoph Perger, Florian Kraxner, Michael Obersteiner, Ujjal Deka Baruah, Nitashree Mili, Nripen Ram Kalita, Mapping Cropland in Ethiopia Using Crowdsourcing International Journal of Geosciences. ,vol. 04, pp. 6- 13 ,(2013) , 10.4236/IJG.2013.46A1002
Yifan Fu, Xingquan Zhu, Bin Li, A survey on instance selection for active learning Knowledge and Information Systems. ,vol. 35, pp. 249- 283 ,(2013) , 10.1007/S10115-012-0507-8
William A. Gale, David D. Lewis, A sequential algorithm for training text classifiers international acm sigir conference on research and development in information retrieval. pp. 3- 12 ,(1994) , 10.5555/188490.188495
John M. Henderson, Andrew Hollingworth, HIGH-LEVEL SCENE PERCEPTION Annual Review of Psychology. ,vol. 50, pp. 243- 271 ,(1999) , 10.1146/ANNUREV.PSYCH.50.1.243
E.B. Baum, Neural net algorithms that learn in polynomial time from examples and queries IEEE Transactions on Neural Networks. ,vol. 2, pp. 5- 19 ,(1991) , 10.1109/72.80287
David J. C. MacKay, Information-based objective functions for active data selection Neural Computation. ,vol. 4, pp. 590- 604 ,(1992) , 10.1162/NECO.1992.4.4.590
Dana Angluin, Queries and Concept Learning Machine Learning. ,vol. 2, pp. 319- 342 ,(1988) , 10.1023/A:1022821128753