Journal of Optoelectronics · Laser, Volume. 35, Issue 10, 1058(2024)
Block robust tensor principal component analysis based on area projection
[1] [1] SIDIROPOULOS N D, DE LATHAUWER L, FU X, et al. Tensor decomposition for signal processing and machine learning[J]. IEEE Transactions on Signal Processing, 2017, 65(13): 3551-3582.
[2] [2] LI Q, SCHONFEID D. Multilinear discriminant analysis for higher-order tensor data classification[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(12): 2524-2537.
[3] [3] LU Y W, YUAN C, LAI Z H, et al. Nuclear norm-based 2DLPP for image classification[J]. IEEE Transactions on Multimedia, 2017, 19(11): 2391-2403.
[4] [4] QING Y H, LIU W Y. Hyperspectral image classification based on multi-scale residual network with attention mechanism[J]. Remote Sensing, 2021, 13(3): 335.
[5] [5] ZARE A, OZDEMIR A, IWEN M A, et al. Extension of PCA to higher order data structures: an introduction to tensors, tensor decompositions, and tensor PCA[J]. Proceedings of the IEEE, 2018, 106(8): 1341-1358.
[6] [6] GOTTUMUKKAL R, ASARI V K. An improved face recognition technique based on modular PCA approach[J]. Pattern Recognition Letters, 2004, 25(4): 429-436.
[7] [7] YANG J, ZHANG D, FRANGI A F, et al. Two-dimensional PCA: a new approach to appearance-based face representation and recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(1): 131-137.
[8] [8] LI X L, PANG Y W, YUAN Y. L1-norm-based 2DPCA[J]. IEEE Transactions on Systems Man and Cybernetics, Part B (Cybernetics), 2010, 40(4): 1170-1175.
[9] [9] WANG R, NIE F P, YANG X J, et al. Robust 2DPCA with non-greedy L1-norm maximization for image analysis[J]. IEEE Transactions on Cybernetics, 2015, 45(5): 1108-1112.
[10] [10] WANG J. Generalized 2-D principal component analysis by LP-norm for image analysis[J]. IEEE Transactions on Cybernetics, 2016, 46(3): 792-803.
[11] [11] LI T, LI M Y, GAO Q X, et al. F-norm distance metric based robust 2DPCA and face recognition[J]. Neural Networks, 2017, 94: 204-211.
[13] [13] LU H P, PLATANIOTIS K N, VENETSANOPOULOS A N. MPCA: multilinear principal component analysis of tensor objects[J]. IEEE Transactions on Neural Networks, 2008, 19(1): 18-39.
[14] [14] PANG Y W, LI X L, YUAN Y. Robust tensor analysis with L1-norm[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2010, 20(2): 172-178.
[15] [15] ZHAO L M, JIA W M, WANG R, et al. Robust tensor analysis with non-greedy L1-norm maximization[J]. Radioengineering, 2016, 25(1): 200-207.
[16] [16] TANG G Y, LU G F, WANG Z Q, et al. Robust tensor prin-cipal component analysis by LP-norm for image analysis[C]//2016 2nd IEEE International Conference on Computer and Communications, October 14-17, 2016, Chengdu, China. New York: IEEE, 2016: 568-573.
[17] [17] GE W M, LI J X, WANG X F. Robust tensor principal component analysis based on F-norm[C]//Proceedings of 2020 IEEE International Conference on Mechatronics and Automation, October 13-16, 2020, Beijing, China. New York: IEEE, 2020: 1077-1082.
Get Citation
Copy Citation Text
ZHANG Xiaomin, ZHANG Chao, SHI Leyan, WANG Xiaofeng. Block robust tensor principal component analysis based on area projection[J]. Journal of Optoelectronics · Laser, 2024, 35(10): 1058
Category:
Received: Aug. 2, 2023
Accepted: Dec. 31, 2024
Published Online: Dec. 31, 2024
The Author Email: