Xinwei Jiang

For Perspective Students: If you are interested into machine learning and image analysis, please drop me email.

News

• Two papers submitted to TGRS and PR.

Publications

Journal Papers

[26]. Superpixelwise PCA based Data Augmentation for Hyperspectral Image Classification
Shang Gao, Xinwei Jiang*, Yongshan Zhang, Xiaobo Liu, Qianjin Xiong and Zhihua Cai
Multimedia Tools and Applications. In press. 2024.
[code]

[25]. Metric learning and local enhancement based collaborative representation for hyperspectral image classification
Jiang Li, Ning Wang, Sai Gong, Xinwei Jiang*, Dongmei Zhang
Multimedia Tools and Applications. In press. 2023.

[24]. MO-CNN: Multiobjective Optimization of Convolutional Neural Networks for Hyperspectral Image Classification
Xiaobo Liu, Xin Gong, Antonio Plaza, Zhihua Cai, Xiao Xiao, Xinwei Jiang, Xiang Liu
IEEE Transactions on Geoscience and Remote Sensing. Vol. 60: 1-14, 2022.

[23]. Unsupervised Dimensionality Reduction for Hyperspectral Imagery via Laplacian Regularized Collaborative Representation Projection
Xinwei Jiang, Liwen Xiong, Qin Yan, Yongshan Zhang, Xiaobo Liu and Zhihua Cai
IEEE Geoscience and Remote Sensing Letters. Vol. 19: 1-5, 2022.
[paper] [code]

[22]. Hypergraph-Structured Autoencoder for Unsupervised and Semisupervised Classification of Hyperspectral Image
Yaoming Cai, Zijia Zhang, Zhihua Cai, Xiaobo Liu and Xinwei Jiang
IEEE Geoscience and Remote Sensing Letters. Vol. 19: 1-5, 2022.

[21]. Marginalized Graph Self-Representation for Unsupervised Hyperspectral Band Selection
Yongshan Zhang, Xinxin Wang, Xinwei Jiang, and Yicong Zhou
IEEE Transactions on Geoscience and Remote Sensing. Vol. 60: 1-12, 2022.

[20]. Classification of hyperspectral images using a propagation filter and convolutional neural network
Qin Yan, Ning Wang, Xinwei Jiang*, Yaoming Cai, Yongshan Zhang, Xiaobo Liu and Zhihua Cai*
Remote Sensing Letters. Vol. 13(5): 429-440, 2022.
[paper] [code]

[19]. Spectral-Spatial and Superpixelwise PCA for Unsupervised Feature Extraction of Hyperspectral Imagery
Xin Zhang, Xinwei Jiang*, Junjun Jiang, Yongshan Zhang, Xiaobo Liu and Zhihua Cai
IEEE Transactions on Geoscience and Remote Sensing. Vol. 60: 1-10, 2022.(ESI Highly Cited Paper)
[paper] [supplementary] [code]

[18]. Latent representation learning based autoencoder for unsupervised feature selection in hyperspectral imagery
Xinxin Wang, Zhenyu Wang, Yongshan Zhang, Xinwei Jiang and Zhihua Cai
Multimedia Tools and Applications. In press. 2021.

[17]. Minimum unbiased risk estimate based 2DPCA for color image denoising
Mingli Wang, Xinwei Jiang, Junbin Gao, Tianjiang Wang, Chunlong Hu, Fang Liu and Qi Feng
Neurocomputing. Vol. 440(14): 127-144. 2021.

[16]. Low rank representation and discriminant analysis-based models for peer-to-peer default risk assessment
Gui Yuan, Shali Huang, Jing Fu and Xinwei Jiang*
Journal of Systems and Information Technology. In press. 2021.

[15]. 一种基于改进双边滤波的鲁棒高光谱遥感图像特征提取方法
陈志坤, 江俊君, 姜鑫维, 白露, 蔡之华
武汉大学学报信息科学版.Vol. 45(4): 504-510. 2020.

[14]. Gaussian Processes Proxy Model with Latent Variable Models and Variogram-Based Sensitivity Analysis for Assisted History Matching
Dongmei Zhang, Yuyang Zhang, Bohou Jiang, Xinwei Jiang* and Zhijiang Kang
Energies. Vol.13(17): 4290. 2020.

[13]. Gaussian Process Graph-Based Discriminant Analysis for Hyperspectral Images Classification
Xin Song, Xinwei Jiang, Junbin Gao and Zhihua Cai
Remote Sensing. Vol.11(9): 2288. 2019.

[12]. Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral Image
Yaoming Cai, Zijia Zhang, Zhihua Cai, Xiaobo Liu, Xinwei Jiang and Qin Yan
IEEE Transactions on Geoscience and Remote Sensing. In press. 2020.

[11]. Trilateral Smooth Filtering for Hyperspectral Image Feature Extraction
Zhikun Chen, Junjun Jiang, Chong Zhou, Xinwei Jiang, Shaoyuan Fu and Zhihua Cai
IEEE Geoscience and Remote Sensing Letters. Vol.16(7): 781-785. 2019.

[10]. Spectral-Spatial Hyperspectral Image Classification with Superpixel Pattern and Extreme Learning Machine
Yongshan Zhang, Xinwei Jiang, Xinxin Wang and Zhihua Cai
Remote Sensing. Vol.11(17):1983. 2019.

[9]. Laplacian Regularized Spatial-Aware Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery
Xinwei Jiang, Xin Song, Yongshan Zhang, Junjun Jiang, Junbin Gao and Zhihua Cai
Remote Sensing. Vol.11(1):29. 2019.

[8]. Spectral-Spatial Feature Extraction of Hyperspectral Images Based on Propagation Filter
Zhikun Chen, Junjun Jiang, Xinwei Jiang, Xiaoping Fang and Zhihua Cai
Sensors. Vol. 18(6): 1978. 2018.

[7]. Efficient history matching with dimensionality reduction methods for reservoir simulations
Dongmei Zhang, Ao Shen, Xinwei Jiang* and Zhijiang Kang
SIMULATION: Transactions of The Society for Modeling and Simulation International. Vol. 94(8): 739-751. 2018.

[6]. Supervised Gaussian Process Latent Variable Model for Hyperspectral Image Classification
Xinwei Jiang, Xiaoping Fang, Zhikun Chen, Junbin Gao, Junjun Jiang and Zhihua Cai
IEEE Geoscience and Remote Sensing Letters. Vol. 14(10): 1760-1764. 2017.

[5]. Noise Robust Face Image Super-Resolution Through Smooth Sparse Representation
Junjun Jiang, Jiayi Ma, Chen Chen, Xinwei Jiang, and Zheng Wang
IEEE Transactions on Cybernetics. Vol.47(11): 3991-4002. 2017.

[4]. Spatial-Aware Collaborative Representation for Hyperspectral Remote Sensing Image Classification
Junjun Jiang, Chen Chen, Yi Yu, Xinwei Jiang, and Jiayi Ma
IEEE Geoscience and Remote Sensing Letters. Vol.14(3): 404-408. 2017.

[3]. TPSLVM: A Dimensionality Reduction Algorithm Based On Thin Plate Splines
Xinwei Jiang, Junbin Gao, Tianjiang Wang, Daming Shi
IEEE Transactions on Cybernetics. Vol. 44(10): 1795 - 1807. 2014.

[2]. Fast identification algorithms for Gaussian process model
Xia Hong, Junbin Gao, Xinwei Jiang, Chris J. Harris
Neurocomputing. Vol. 133(10):25-31. 2014.

[1]. Supervised Latent Linear Gaussian Process Latent Variable Model for Dimensionality Reduction
Xinwei Jiang, Junbin Gao, Tianjiang Wang
IEEE Transactions on Systems, Man, and Cybernetics, Part B. Vol. 42(6): 1620-1632. 2012.
[paper] [slides] [code] [data] [project page]

Conference Papers

[5]. Shared Deep Kernel Learning for Dimensionality Reduction
Xinwei Jiang, Junbin Gao, Xiaobo Liu, Zhihua Cai, Dongmei Zhang and Yuanxing Liu
The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). 2018.

[4]. Nonparametrically Guided Autoencoder with Laplace Approximation For Dimensionality Reduction
Xinwei Jiang, Xin Song, Junbin Gao, Zhihua Cai, Dongmei Zhang
The 2016 International Joint Conference on Neural Networks (IJCNN), 2016

[3]. Gaussian Processes Autoencoder for Dimensionality Reduction
Xinwei Jiang, Junbin Gao, Xia Hong, Zhihua Cai
The 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015

[2]. Thin Plate Spline Latent Variable Models for Dimensionality Reduction
Xinwei Jiang, Junbin Gao, Daming Shi, Tianjiang Wang
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012

[1]. Learning Gradients with Gaussian Processes
Xinwei Jiang, Junbin Gao, Daming Shi, Tianjiang Wang
The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2010

Dissertation

Funds

• 2022.1.1-2023.12.31, Research on small-sample hyperspectral remote sensing of UAV for smart agriculture, National Science Foundation of Hubei, PI
• 2016.1.1-2020.12.31, Evaluation of interwell connectivity for fracture-cavity reservoirs, National Science and Technology Major Project of China, Rank 3
• 2015.1.1-2017.12.31, Research on Kernel Methods Based Deep Learning Algorithms for Dimensionality Reduction, National Natural Science Foundation of China, PI

Talks

Teaching

• Fall 2022, - Data Structures
• Fall 2021, - Data Structures
• Fall 2020, - Data Structures
• Fall 2019, - Data Structures - A
• Spring 2017, - Data Structures - B
• Fall 2016, - Data Structures
• Fall 2016, - Data Structures - B
• Fall 2015, - Data Structures
• Spring 2015, - Data Structures - B
• Fall 2014, - Data Structures
• Fall 2014, - Introduction to Computer Programming (C)

Education

Experience

Graduated Students

Other Stuff