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Yang, Yazhou, Loog, Marco (2019) Single shot active learning using pseudo annotators. Pattern Recognition, 89. 22-31 doi:10.1016/j.patcog.2018.12.027

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Reference TypeJournal (article/letter/editorial)
TitleSingle shot active learning using pseudo annotators
JournalPattern Recognition
AuthorsYang, YazhouAuthor
Loog, MarcoAuthor
Year2019 (May)Volume89
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2018.12.027Search in ResearchGate
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Mindat Ref. ID9367702Long-form Identifiermindat:1:5:9367702:0
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Full ReferenceYang, Yazhou, Loog, Marco (2019) Single shot active learning using pseudo annotators. Pattern Recognition, 89. 22-31 doi:10.1016/j.patcog.2018.12.027
Plain TextYang, Yazhou, Loog, Marco (2019) Single shot active learning using pseudo annotators. Pattern Recognition, 89. 22-31 doi:10.1016/j.patcog.2018.12.027
In(2019) Pattern Recognition Vol. 89. Elsevier BV

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Yang, Yazhou, Loog, Marco (2022) To Actively Initialize Active Learning. Pattern Recognition, 131. 108836 doi:10.1016/j.patcog.2022.108836
Yang, Yazhou, Loog, Marco (2018) A variance maximization criterion for active learning. Pattern Recognition, 78. 358-370 doi:10.1016/j.patcog.2018.01.017
Yang, Yazhou, Loog, Marco (2018) A benchmark and comparison of active learning for logistic regression. Pattern Recognition, 83. 401-415 doi:10.1016/j.patcog.2018.06.004
Cheplygina, Veronika, Tax, David M.J., Loog, Marco (2015) Multiple instance learning with bag dissimilarities. Pattern Recognition, 48 (1). 264-275 doi:10.1016/j.patcog.2014.07.022
Alpaydın, Ethem, Cheplygina, Veronika, Loog, Marco, Tax, David M.J. (2015) Single- vs. multiple-instance classification. Pattern Recognition, 48 (9). 2831-2838 doi:10.1016/j.patcog.2015.04.006
Wu, Jianxin, Bai, Xiang, Loog, Marco, Roli, Fabio, Zhou, Zhi-Hua (2017) Editorial of the Special Issue on Multi-instance Learning in Pattern Recognition and Vision. Pattern Recognition, 71. 444-445 doi:10.1016/j.patcog.2017.05.026
Li, Yan, Tax, David M.J., Duin, Robert P.W., Loog, Marco (2013) Multiple-instance learning as a classifier combining problem. Pattern Recognition, 46 (3). 865-874 doi:10.1016/j.patcog.2012.08.018
Cui, Zhiyan, Lu, Na, Wang, Weifeng (2022) Pseudo loss active learning for deep visual tracking. Pattern Recognition, 130. 108773 doi:10.1016/j.patcog.2022.108773
Krijthe, Jesse H., Loog, Marco (2017) Robust semi-supervised least squares classification by implicit constraints. Pattern Recognition, 63. 115-126 doi:10.1016/j.patcog.2016.09.009
Loog, Marco, van Ginneken, Bram, Duin, Robert P.W. (2005) Dimensionality reduction of image features using the canonical contextual correlation projection. Pattern Recognition, 38 (12). 2409-2418 doi:10.1016/j.patcog.2005.04.011
Loog, Marco (2007) On an alternative formulation of the Fisher criterion that overcomes the small sample problem. Pattern Recognition, 40 (6). 1753-1755 doi:10.1016/j.patcog.2006.11.002
 
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