[1] A. Volkova, J. Baird, I. Wajchman and J. Guinane, Comparison of Aerial Hyperspectral and Multispectral Imagery: Case Study of Nitrogen Mapping in Australian Cotton, 2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Amsterdam, Netherlands, pp. 1-5, 2018.
[2] L. Sun, Z. Ma and Y. Zhang, ABLAL: Adaptive Background Latent Space Adversarial Learning Algorithm for Hyperspectral Target Detection, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 411-427, 2024.
[3] M. Imani, Manifold Structure Preservative for Hyperspectral Target Detection, Advances in Space Research, vol. 61, pp. 2510–2520, 2018.
[4] N. M. Nasrabadi, Hyperspectral Target Detection: An Overview of Current and Future Challenges, in IEEE Signal Processing Magazine, vol. 31, no. 1, pp. 34-44, Jan. 2014.
[5] A. Zare, C. Jiao and T. Glenn, Discriminative Multiple Instance Hyperspectral Target Characterization, in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 10, pp. 2342-2354, Oct. 2018.
[6] F. Wang, J. Chen and K. Sun, Hyperspectral Anomaly Detection Based on Adaptive Subspace Detector, 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC), Xiamen, China, 2019, pp. 257-260.
[7] X. Yang, J. Chen and Z. He, Sparse-SpatialCEM for Hyperspectral Target Detection, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 7, pp. 2184-2195, July 2019.
[8] X. Zhao, W. Li, C. Zhao and R. Tao, Hyperspectral Target Detection Based on Weighted Cauchy Distance Graph and Local Adaptive Collaborative Representation, in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-13, Art no. 5527313, 2022.
[9] M. Imani, A Shaped Collaborative Representation-Based Detector for Hyperspectral Anomaly Detection, Remote Sensing Letters, vol. 14, no. 11, pp. 1162-1172, 2023.
[10] C. Li, W. Zhang, Y. Zhang, Z. Chen and H. Gao, Adaptively Dictionary Construction for Hyperspectral Target Detection, in IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1-5, Art no. 5502005, 2023.
[11] M. Imani, Sparse and collaborative representation-based anomaly detection, Signal Image and Video Processing, vol. 14, no. 8, pp. 1573–1581, 2020.
[12] W. Li, Q. Du, B. Zhang, Combined sparse and collaborative representation for hyperspectral target detection, Pattern Recognition, vol. 48, no. 12, pp. 3904–3916, 2015.
[13] J. Zhao, G. Wang, B. Zhou, J. Ying and J. Liu, SRA–CEM: An Improved CEM Target Detection Algorithm for Hyperspectral Images Based on Subregion Analysis, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 6026-6037, 2023.
[14] B. Chen, L. Liu, Z. Zou, Z. Shi, Target Detection in Hyperspectral Remote Sensing Image: Current Status and Challenges, Remote Sensing, vol. 15, no. 13, 3223, 2023.
[15] D. Wang, L. Zhuang, L. Gao, X. Sun, X. Zhao and A. Plaza, Sliding Dual-Window-Inspired Reconstruction Network for Hyperspectral Anomaly Detection, in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-15, Art no. 5504115, 2024.
[16] B. Khosravi, M. Imani, H. Ghassemian, Shaped Patch Based Nonparametric Discriminant Analysis for Hyperspectral Image Classification through the CNN Model, International Journal of Remote Sensing, vol. 44, no. 6, pp. 1789–1819, 2023.
[17] Y. Gao, Y. Feng, X. Yu and S. Mei, Robust Signature-Based Hyperspectral Target Detection Using Dual Networks, in IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1-5, Art no. 5500605, 2023.
[18] Y. Shi, K. Wang, J. Li and Y. Li, Hyperspectral Target Detection with Hierarchical Denoising Autoencoder and Subspace Projection, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, pp. 4404-4407, 2021.
[19] Z. Wang, D. Ma, G. Yue, B. Li, R. Cong and Z. Wu, Self-Supervised Hyperspectral Anomaly Detection Based on Finite Spatialwise Attention, in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-18, Art no. 5502918, 2024.
[20] H. Qin, W. Xie, Y. Li, K. Jiang, J. Lei and Q. Du, PTGAN: A Proposal-Weighted Two-Stage GAN with Attention for Hyperspectral Target Detection, 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium, pp. 4428-4431, 2021.
[21] Y. Gao, Y. Feng, X. Yu, Hyperspectral Target Detection with an Auxiliary Generative Adversarial Network" Remote Sensing, vol. 13, no. 21: 4454, 2021.
[22] T. Jiang, Y. Li, W. Xie and Q. Du, Discriminative Reconstruction Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection, IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 7, pp. 4666-4679, July 2020.
[23] X. Zhang, K. Gao, J. Wang, Z. Hu, H. Wang, P. Wang, Siamese Network Ensembles for Hyperspectral Target Detection with Pseudo Data Generation. Remote Sensing, vol. 14, no. 5, 1260, 2022.
[24] J. Xu, Z. Li, B. Du, M. Zhang and J. Liu, Reluplex made more practical: Leaky ReLU, 2020 IEEE Symposium on Computers and Communications (ISCC), Rennes, France, pp. 1-7, 2020.
[25] K. Sanjar, A. Rehman, A. Paul and K. JeongHong, Weight Dropout for Preventing Neural Networks from Overfitting, 2020 8th International Conference on Orange Technology (ICOT), Daegu, Korea (South), pp. 1-4, 2020.
[26] Y. Chen, H. Jiang, C. Li, X. Jia and P. Ghamisi, Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks, in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 10, pp. 6232-6251, Oct. 2016.
[27] M. Imani, Difference-Based Target Detection Using Mahalanobis Distance and Spectral Angle, International Journal of Remote Sensing, vol. 40, no. 3, pp. 811-831, 2019.
[28] M. Fahad, M. He and Y. Zhang, Combination of CEM & RXD for target detection in hyperspectral images, 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Los Angeles, CA, USA, pp. 1-4, 2016.
[29] M. Imani, H. Ghassemian, Improved PCA method using clustering for feature extraction of hyperspectral remote sensing images, Geomatics 94, Tehran, Iran, May 2015.