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Volumn 2016-November, Issue , 2016, Pages 469-472

Active learning based autoencoder for hyperspectral imagery classification

Author keywords

active learning; Autoencoder; deep learning; hyperspectral imagery classification

Indexed keywords


EID: 85007467133     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2016.7729116     Document Type: Conference Paper
Times cited : (26)

References (15)
  • 2
    • 77957741951 scopus 로고
    • On the mean accuracy of statistical pattern recognizers
    • Gordon P Hughes, "On the mean accuracy of statistical pattern recognizers, " Information Theory, IEEE Transactions on, vol. 14, no. 1, pp. 55-63, 1968.
    • (1968) Information Theory, IEEE Transactions on , vol.14 , Issue.1 , pp. 55-63
    • Hughes, G.P.1
  • 3
    • 70350336222 scopus 로고    scopus 로고
    • Clustering-based extraction of border training patterns for accurate SVM classification of hyperspectral images
    • B. Demir and S. Erturk, "Clustering-based extraction of border training patterns for accurate svm classification of hyperspectral images, " IEEE Geoscience and Remote Sensing Letters, vol. 6, no. 4, pp. 840-844, 2009.
    • (2009) IEEE Geoscience and Remote Sensing Letters , vol.6 , Issue.4 , pp. 840-844
    • Demir, B.1    Erturk, S.2
  • 4
    • 84901748579 scopus 로고    scopus 로고
    • Classification of hyperspectral imagery with neural networks: Comparison to conventional tools
    • Erzsébet Merényi, William H Farrand, James V Taranik, and Timothy B Minor, "Classification of hyperspectral imagery with neural networks: comparison to conventional tools, " EURASIP Journal on Advances in Signal Processing, vol. 2014, no. 1, pp. 1-19, 2014.
    • (2014) EURASIP Journal on Advances in Signal Processing , vol.2014 , Issue.1 , pp. 1-19
    • Merényi, E.1    Farrand, W.H.2    Taranik, J.V.3    Minor, T.B.4
  • 5
    • 84869489944 scopus 로고    scopus 로고
    • Semisupervised hyperspectral image classification using soft sparse multinomial logistic regression
    • Jun Li, José M Bioucas-Dias, and Antonio Plaza, "Semisupervised hyperspectral image classification using soft sparse multinomial logistic regression, " Geoscience and Remote Sensing Letters, IEEE, vol. 10, no. 2, pp. 318-322, 2013.
    • (2013) Geoscience and Remote Sensing Letters, IEEE , vol.10 , Issue.2 , pp. 318-322
    • Li, J.1    Bioucas-Dias, J.M.2    Plaza, A.3
  • 6
    • 84930630277 scopus 로고    scopus 로고
    • Deep learning
    • Yann LeCun, Yoshua Bengio, and Geoffrey Hinton, "Deep learning, " Nature, vol. 521, no. 6, pp. 436-444, 2015.
    • (2015) Nature , vol.521 , Issue.6 , pp. 436-444
    • LeCun, Y.1    Bengio, Y.2    Hinton, G.3
  • 10
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • Geoffrey E Hinton and Ruslan R Salakhutdinov, "Reducing the dimensionality of data with neural networks, " Science, vol. 313, no. 5786, pp. 504-507, 2006.
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 12
    • 84939141053 scopus 로고    scopus 로고
    • Deep convolutional neural networks for hyperspectral image classification
    • Wei Hu, Yangyu Huang, Li Wei, Fan Zhang, and Hengchao Li, "Deep convolutional neural networks for hyperspectral image classification, " Journal of Sensors, vol. 501, pp. 258619, 2015.
    • (2015) Journal of Sensors , vol.501 , pp. 258619
    • Hu, W.1    Huang, Y.2    Wei, L.3    Zhang, F.4    Li, H.5
  • 13
    • 80053562930 scopus 로고    scopus 로고
    • Hyperspectral image segmentation using a new Bayesian approach with active learning
    • Jun Li, José M Bioucas-Dias, and Antonio Plaza, "Hyperspectral image segmentation using a new Bayesian approach with active learning, " Geoscience and Remote Sensing, IEEE Transactions on, vol. 49, no. 10, pp. 3947-3960, 2011.
    • (2011) Geoscience and Remote Sensing, IEEE Transactions on , vol.49 , Issue.10 , pp. 3947-3960
    • Li, J.1    Bioucas-Dias, J.M.2    Plaza, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.