Books

Jia X; Richards JA, 1999, Remote Sensing Digital Image Analysis, Original, Springer-Verlag, Berlin, Germany

Book Chapters

Jia X, 2017, 'Supervised classification', in Richardson D (ed.), International Encyclopedia of Geography, 15 Volume Set People, the Earth, Environment and Technology, John Wiley & Sons

Sarker CD; Jia X; Fraser D, 2015, 'Spectral unmixing with estimated adaptive endmember index using extended support vector machine', in Dutt AK; Noble A; Costa F; Thakur S; Thakur R; Sharma HA (ed.), Spatial Diversity and Dynamics in Resources and Urban Development: Volume 1: Regional Resources, Springer, pp. 37 - 72, http://dx.doi.org/10.1007/978-94-017-9771-9

Ng TF; Jia X; Fraser D; Pham TD, 2013, 'Fuzzy knowledge-based subspace clustering for life science data analysis', in Pham TD; Jain LC (ed.), Knowledge-Based Systems in Biomedicine and Computational Life Science, Springer, pp. 177 - 213, http://dx.doi.org/10.1007/978-3-642-33015-5_8

Li F; Jia X; Fraser D; Lambert AJ, 2012, 'Super Resolution for multispectral image classification', in Gunturk BK; Li X (ed.), Image Restoration: fundamentals and advances, edn. 1, CRC Press, pp. 217 - 247

Jia X; Richards J, 2007, 'Hyperspectral Data Representation', in Chang CI (ed.), Hyperspectral Data Exploitation ? Theory and Applications, John Wiley & Sons, Hoboken, New Jersey, USA, pp. 205 - 225, http://dx.doi.org/10.1002/9780470124628.ch8

Wang L; Jia X; Zhang Y, 2006, 'Construction of Fast and Robust N-FINDR Algorithm', in Huang D; Irwin G (ed.), Intelligent Computing in Signal Processing and Pattern Recognition International Conference on Intelligent Computing, August, 2006, Springer Verlag, pp. 791 - 796

Journal articles

Xie W; Li Y; Lei J; Yang J; Li J; Jia X; Li Z, 2020, 'Unsupervised spectral mapping and feature selection for hyperspectral anomaly detection', Neural Networks, vol. 132, pp. 144 - 154, http://dx.doi.org/10.1016/j.neunet.2020.08.010

Wang L; Wang S; Jia X; Li X, 2020, 'Twin support vector machine-based hyperspectral unmixing and its uncertainty analysis', Journal of Applied Remote Sensing, vol. 14, http://dx.doi.org/10.1117/1.JRS.14.046504

Hu J; Jia X; Li Y; He G; Zhao M, 2020, 'Hyperspectral Image Super-Resolution via Intrafusion Network', IEEE Transactions on Geoscience and Remote Sensing, vol. 58, pp. 7459 - 7471, http://dx.doi.org/10.1109/TGRS.2020.2982940

Guo Y; Zhang J; Awan AF; Chen X; Jia X, 2020, 'Activities of the IEEE GRSS University of New South Wales Canberra Student Chapter [Chapters]', IEEE Geoscience and Remote Sensing Magazine, vol. 8, pp. 102 - 103, http://dx.doi.org/10.1109/MGRS.2020.2997823

Zhang J; Jia X; Hu J; Chanussot J, 2020, 'Online structured sparsity-based moving-object detection from satellite videos', IEEE Transactions on Geoscience and Remote Sensing, vol. 58, pp. 6420 - 6433, http://dx.doi.org/10.1109/TGRS.2020.2976855

Jia S; Jia S; Jia S; Jia S; Deng X; Xu M; Xu M; Xu M; Xu M; Zhou J; Jia X, 2020, 'Superpixel-level weighted label propagation for hyperspectral image classification', IEEE Transactions on Geoscience and Remote Sensing, vol. 58, pp. 5077 - 5091, http://dx.doi.org/10.1109/TGRS.2020.2972294

Tan K; Niu C; Jia X; Ou D; Chen Y; Lei S, 2020, 'Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China', ISPRS Journal of Photogrammetry and Remote Sensing, vol. 165, pp. 1 - 15, http://dx.doi.org/10.1016/j.isprsjprs.2020.04.022

Zhang J; Jia X; Hu J, 2020, 'Error Bounded Foreground and Background Modeling for Moving Object Detection in Satellite Videos', IEEE Transactions on Geoscience and Remote Sensing, vol. 58, pp. 2659 - 2669, http://dx.doi.org/10.1109/TGRS.2019.2953181

Huang X; Li S; Li J; Jia X; Li J; Zhu XX; Benediktsson JA, 2020, 'A Multispectral and Multiangle 3-D Convolutional Neural Network for the Classification of ZY-3 Satellite Images Over Urban Areas', IEEE Transactions on Geoscience and Remote Sensing, http://dx.doi.org/10.1109/TGRS.2020.3037211

Fu H; Sun G; Zabalza J; Zhang A; Ren J; Jia X, 2020, 'A Novel Spectral-Spatial Singular Spectrum Analysis Technique for near Real-Time in Situ Feature Extraction in Hyperspectral Imaging', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 2214 - 2225, http://dx.doi.org/10.1109/JSTARS.2020.2992230

Wang M; Tan K; Jia X; Wang X; Chen Y, 2020, 'A deep Siamese network with hybrid convolutional feature extraction module for change detection based on multi-sensor remote sensing images', Remote Sensing, vol. 12, pp. 205 - 205, http://dx.doi.org/10.3390/rs12020205

Ren J; Hussain A; Han J; Jia X, 2019, 'Cognitive Modelling and Learning for Multimedia Mining and Understanding', Cognitive Computation, vol. 11, pp. 761 - 762, http://dx.doi.org/10.1007/s12559-019-09684-6

Chen Y; Huang L; Zhu L; Yokoya N; Jia X, 2019, 'Fine-grained classification of hyperspectral imagery based on deep learning', Remote Sensing, vol. 11, http://dx.doi.org/10.3390/rs11222690

Jia S; Zhuang J; Deng L; Zhu J; Xu M; Zhou J; Jia X, 2019, '3-D Gaussian-Gabor Feature Extraction and Selection for Hyperspectral Imagery Classification', IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 8813 - 8826, http://dx.doi.org/10.1109/TGRS.2019.2923213

Xie W; Lei J; Liu B; Li Y; Jia X, 2019, 'Spectral constraint adversarial autoencoders approach to feature representation in hyperspectral anomaly detection', Neural Networks, vol. 119, pp. 222 - 234, http://dx.doi.org/10.1016/j.neunet.2019.08.012

Zhang J; Jia X; Hu J, 2019, 'Local Region Proposing for Frame-Based Vehicle Detection in Satellite Videos', Remote Sensing, vol. 11, pp. 2372 - 2372, http://dx.doi.org/10.3390/rs11202372

Jia S; Deng X; Zhu J; Xu M; Zhou J; Jia X, 2019, 'Collaborative representation-based multiscale superpixel fusion for hyperspectral image classification', IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 7770 - 7784, http://dx.doi.org/10.1109/TGRS.2019.2916329

Gao Q; Lim S; Jia X, 2019, 'Spectral-spatial hyperspectral image classification using a multiscale conservative smoothing scheme and adaptive sparse representation', IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 7718 - 7730, http://dx.doi.org/10.1109/TGRS.2019.2915809

Guo Y; Jia X; Paull D; Benediktsson JA, 2019, 'Nomination-favoured opinion pool for optical-SAR-synergistic rice mapping in face of weakened flooding signals', ISPRS Journal of Photogrammetry and Remote Sensing, vol. 155, pp. 187 - 205, http://dx.doi.org/10.1016/j.isprsjprs.2019.07.008

H. Trisasongko B; J. Paull D; Griffin AL; Jia X; Panuju DR, 2019, 'On the relationship between the circumference of rubber trees and L-band waves', International Journal of Remote Sensing, vol. 40, pp. 6395 - 6417, http://dx.doi.org/10.1080/01431161.2019.1591650

Xie W; Jia X; Li Y; Lei J, 2019, 'Hyperspectral Image Super-Resolution Using Deep Feature Matrix Factorization', IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 6055 - 6067, http://dx.doi.org/10.1109/TGRS.2019.2904108

Xie W; Jiang T; Li Y; Jia X; Lei J, 2019, 'Structure Tensor and Guided Filtering-Based Algorithm for Hyperspectral Anomaly Detection', IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 4218 - 4230, http://dx.doi.org/10.1109/TGRS.2018.2890212

Chen Y; Wang Y; Gu Y; He X; Ghamisi P; Jia X, 2019, 'Deep Learning Ensemble for Hyperspectral Image Classification', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, pp. 1882 - 1897, http://dx.doi.org/10.1109/JSTARS.2019.2915259

Li J; Huang X; Hu T; Jia X; Benediktsson JA, 2019, 'A novel unsupervised sample collection method for urban land-cover mapping using landsat imagery', IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 3933 - 3951, http://dx.doi.org/10.1109/TGRS.2018.2889109

Sun G; Huang H; Weng Q; Zhang A; Jia X; Ren J; Sun L; Chen X, 2019, 'Combinational shadow index for building shadow extraction in urban areas from Sentinel-2A MSI imagery', International Journal of Applied Earth Observation and Geoinformation, vol. 78, pp. 53 - 65, http://dx.doi.org/10.1016/j.jag.2019.01.012

Deng Y; Wu C; Zhang X; Jia X, 2019, 'Examining the effectiveness of weighted spectral mixture analysis (WSMA) in urban environments', International Journal of Remote Sensing, vol. 40, pp. 3055 - 3075, http://dx.doi.org/10.1080/01431161.2018.1539270

Tien Bui D; Shahabi H; Omidvar E; Shirzadi A; Geertsema M; Clague J; Khosravi K; Pradhan B; Pham B; Chapi K; Barati Z; Bin Ahmad B; Rahmani H; Gróf G; Lee S, 2019, 'Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm', Remote Sensing, vol. 11, pp. 931 - 931, http://dx.doi.org/10.3390/rs11080931

Zhang A; Sun G; Ma P; Jia X; Ren J; Huang H; Zhang X, 2019, 'Coastal wetland mapping with Sentinel-2 MSI imagery based on gravitational optimized multilayer perceptron and morphological attribute profiles', Remote Sensing, vol. 11, pp. 1 - 23, http://dx.doi.org/10.3390/rs11080952

Xie W; Shi Y; Li Y; Jia X; Lei J, 2019, 'High-quality spectral-spatial reconstruction using saliency detection and deep feature enhancement', Pattern Recognition, vol. 88, pp. 139 - 152, http://dx.doi.org/10.1016/j.patcog.2018.11.004

Luo X; Yin J; Luo X; Jia X, 2019, 'A novel adversarial based hyperspectral and multispectral image fusion', Remote Sensing, vol. 11, http://dx.doi.org/10.3390/rs11050492

Xu M; Jia X; Pickering M; Jia S, 2019, 'Thin cloud removal from optical remote sensing images using the noise-adjusted principal components transform', ISPRS Journal of Photogrammetry and Remote Sensing, vol. 149, pp. 215 - 225, http://dx.doi.org/10.1016/j.isprsjprs.2019.01.025

Ren J; Jia X; Liao W; Gao L, 2019, 'Guest editorial: Hyperspectral imaging and applications', IET Image Processing, vol. 13, pp. 233 - 234, http://dx.doi.org/10.1049/iet-ipr.2018.6533

Zhu K; Chen Y; Ghamisi P; Jia X; Benediktsson JA, 2019, 'Deep convolutional capsule network for hyperspectral image spectral and spectral-spatial classification', Remote Sensing, vol. 11, http://dx.doi.org/10.3390/rs11030223

Gao L; He Y; Sun X; Jia X; Zhang B, 2019, 'Incorporating negative sample training for ship detection based on deep learning', Sensors (Switzerland), vol. 19, http://dx.doi.org/10.3390/s19030684

Farooq A; Hu J; Jia X, 2019, 'Analysis of Spectral Bands and Spatial Resolutions for Weed Classification Via Deep Convolutional Neural Network', IEEE Geoscience and Remote Sensing Letters, vol. 16, pp. 183 - 187, http://dx.doi.org/10.1109/LGRS.2018.2869879

Jia S; Wu K; Zhu J; Jia X, 2019, 'Spectral-spatial gabor surface feature fusion approach for hyperspectral imagery classification', IEEE Transactions on Geoscience and Remote Sensing, vol. 57, pp. 1142 - 1154, http://dx.doi.org/10.1109/TGRS.2018.2864983

Farooq A; Jia X; Hu J; Zhou J, 2019, 'Multi-resolution weed classification via convolutional neural network and superpixel based local binary pattern using remote sensing images', Remote Sensing, vol. 11, http://dx.doi.org/10.3390/rs11141692

Sun G; Kong Y; Jia X; Zhang A; Rong J; Ma H, 2019, 'Synergistic Use of Optical and Dual-Polarized SAR Data with Multiple Kernel Learning for Urban Impervious Surface Mapping', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, pp. 223 - 236, http://dx.doi.org/10.1109/JSTARS.2018.2883654

Qv H; Yin J; Luo X; Jia X, 2018, 'Band dual density discrimination analysis for hyperspectral image classification', IEEE Transactions on Geoscience and Remote Sensing, vol. 56, pp. 7257 - 7271, http://dx.doi.org/10.1109/TGRS.2018.2849881

Xu J; Hu J; Jia X, 2018, 'A target image–oriented dictionary learning–based method for fully automated latent fingerprint forensic', Computational Intelligence, vol. 34, pp. 1178 - 1198, http://dx.doi.org/10.1111/coin.12177

Xie W; Li Y; Jia X, 2018, 'Deep convolutional networks with residual learning for accurate spectral-spatial denoising', Neurocomputing, vol. 312, pp. 372 - 381, http://dx.doi.org/10.1016/j.neucom.2018.05.115

Alam FI; Zhou J; Liew AWC; Jia X; Chanussot J; Gao Y, 2018, 'Conditional Random Field and Deep Feature Learning for Hyperspectral Image Classification', IEEE Transactions on Geoscience and Remote Sensing, pp. 1 - 17, http://dx.doi.org/10.1109/TGRS.2018.2867679

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