Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics

Olga Mendoza-Schrock; Mateen M. Rizki; Michael L. Raymer; Vincent J. Velten

Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics

Olga Mendoza-Schrock, Mateen M. Rizki, Michael L. Raymer, Vincent J. Velten

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017
Editors	Hamid R. Arabnia, Leonidas Deligiannidis, Fernando G. Tinetti
Publisher	CSREA Press
Pages	3-9
Number of pages	7
ISBN (Electronic)	1601324642, 9781601324641
State	Published - 2017
Externally published	Yes
Event	2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017 - Las Vegas, United States Duration: Jul 17 2017 → Jul 20 2017

Publication series

Name	Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017

Conference

Conference	2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017
Country/Territory	United States
City	Las Vegas
Period	7/17/17 → 7/20/17

ASJC Scopus Subject Areas

Computer Vision and Pattern Recognition
Computer Graphics and Computer-Aided Design

Keywords

Electro-optical imaging
Health informatics
Manifold learning
Transfer learning
Transfer subspace learning

Cite this

Mendoza-Schrock, O., Rizki, M. M., Raymer, M. L., & Velten, V. J. (2017). Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics. In H. R. Arabnia, L. Deligiannidis, & F. G. Tinetti (Eds.), Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017 (pp. 3-9). (Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017). CSREA Press.

Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics. / Mendoza-Schrock, Olga; Rizki, Mateen M.; Raymer, Michael L. et al.
Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017. ed. / Hamid R. Arabnia; Leonidas Deligiannidis; Fernando G. Tinetti. CSREA Press, 2017. p. 3-9 (Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mendoza-Schrock, O, Rizki, MM, Raymer, ML & Velten, VJ 2017, Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics. in HR Arabnia, L Deligiannidis & FG Tinetti (eds), Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017. Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017, CSREA Press, pp. 3-9, 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017, Las Vegas, United States, 7/17/17.

Mendoza-Schrock O, Rizki MM, Raymer ML, Velten VJ. Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics. In Arabnia HR, Deligiannidis L, Tinetti FG, editors, Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017. CSREA Press. 2017. p. 3-9. (Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017).

Mendoza-Schrock, Olga ; Rizki, Mateen M. ; Raymer, Michael L. et al. / Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics. Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017. editor / Hamid R. Arabnia ; Leonidas Deligiannidis ; Fernando G. Tinetti. CSREA Press, 2017. pp. 3-9 (Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017).

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title = "Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics",

keywords = "Electro-optical imaging, Health informatics, Manifold learning, Transfer learning, Transfer subspace learning",

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Manifold transfer subspace learning (MTSL) for high dimensional data—applications to handwritten digits and health informatics

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

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Cite this