[Paper] Evaluation of Deep Feature Reconstruction for Pixel-Wise Hyperspectral Image Classification
Author:
Affiliation:
1. Graduate School of Advanced Science and Technology, Tokyo Denki University
Publisher
Institute of Image Information and Television Engineers
Link
https://www.jstage.jst.go.jp/article/mta/12/3/12_190/_pdf
Reference19 articles.
1. 1) Alcolea, A., Paoletti, M. E., Haut, J. M., Resano, J. and Plaza, A.: Inference in Supervised Spectral Classifiers for On-Board Hyperspectral Imaging: An Overview, Remote Sensing, Vol. 12, No. 3 (2020).
2. 2) Baumgardner, M. F. et al.: 220 Band AVIRIS Hyperspectral Image Data Set: June 12, 1992 Indian Pine Test Site 3 (2015).
3. 3) Cao, F., Yang, Z., Ren, J., Jiang, M. and Ling, W.-K.: Does Normalization Methods Play a Role for Hyperspectral Image Classification?, ArXiv, Vol. abs/1710.02939 (2017).
4. 4) Chehdi, K., Soltani, M. and Cariou, C.: Pixel classification of large-size hyperspectral images by affinity propagation, Journal of applied remote sensing, Vol. 8, No. 1, pp. 083567-083567 (2014).
5. 5) Chen, F., Jiang, H., Van de Voorde, T., Lu, S., Xu, W. and Zhou, Y.: Land cover mapping in urban environments using hyperspectral APEX data: A study case in Baden, Switzerland, International Journal of Applied Earth Observation and Geoinformation, Vol. 71, pp. 70-82 (2018).
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