Items where Author is "Zhou, Jun"

Article

Yang, W., Wu, D., Bai, J., Wang, J., Rong, S. and Zhou, J. (2026) FedDA-HSI: Federated Class-Aware Framework for Hyperspectral Image Classification With Diffusion Augmentation. IEEE Transactions on Geoscience and Remote Sensing, 64 . pp. 1-17. https://doi.org/10.1109/TGRS.2026.3660734

Yang, J. X., Zhou, J., Wang, J., Tian, H. and Liew, A. W.-C. (2024) LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection and Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 62 . pp. 1-15. https://doi.org/10.1109/TGRS.2024.3389651

Bai, S. H., Tahmasbian, I., Zhou, J., Nevenimo, T., Hannet, G., Walton, D., Randall, B., Gama, T. and Wallace, H. M. (2018) A non-destructive determination of peroxide values, total nitrogen and mineral nutrients in an edible tree nut using hyperspectral imaging. Computers and Electronics in Agriculture, 151 . pp. 492-500. https://doi.org/10.1016/j.compag.2018.06.029

Tahmasbian, I., Hosseini Bai, S., Wang, Y., Boyd, S., Zhou, J., Esmaeilani, R. and Xu, Z. (2018) Using laboratory-based hyperspectral imaging method to determine carbon functional group distributions in decomposing forest litterfall. CATENA, 167 . pp. 18-27. https://doi.org/10.1016/j.catena.2018.04.023

Tahmasbian, I., Xu, Z., Boyd, S., Zhou, J., Esmaeilani, R., Che, R. and Hosseini Bai, S. (2018) Laboratory-based hyperspectral image analysis for predicting soil carbon, nitrogen and their isotopic compositions. Geoderma, 330 . pp. 254-263. https://doi.org/10.1016/j.geoderma.2018.06.008

Tahmasbian, I., Xu, Z., Abdullah, K., Zhou, J., Esmaeilani, R., Nguyen, T. T. N. and Hosseini Bai, S. (2017) The potential of hyperspectral images and partial least square regression for predicting total carbon, total nitrogen and their isotope composition in forest litterfall samples. Journal of Soils and Sediments, 17 (8). pp. 2091-2103. https://doi.org/10.1007/s11368-017-1751-z