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Zhiling Long, Ph.D.

Affiliations: 
2007 Electrical and Computer Engineering Mississippi State University, Starkville, MS, United States 
Area:
Electronics and Electrical Engineering
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"Zhiling Long"
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Nicolas H. Younan grad student 2007 Mississippi State University
 (Statistical image modeling in the contourlet domain with application to texture segmentation.)

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Publications

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Alfarraj M, Alaudah Y, Long Z, et al. (2018) Multiresolution analysis and learning for computational seismic interpretation The Leading Edge. 37: 443-450
Long Z, Alaudah Y, Ali Qureshi M, et al. (2018) A comparative study of texture attributes for characterizing subsurface structures in seismic volumes Interpretation. 6: T1055-T1066
Hu Y, Long Z, AlRegib G. (2018) A High-Speed, Real-Time Vision System for Texture Tracking and Thread Counting Ieee Signal Processing Letters. 25: 758-762
Shafiq MA, Alshawi T, Long Z, et al. (2017) The role of visual saliency in the automation of seismic interpretation Geophysical Prospecting. 66: 132-143
Long Z, Alaudah Y, Qureshi MA, et al. (2015) Characterization of Migrated Seismic Volumes using Texture Attributes: A Comparative Study Seg Technical Program Expanded Abstracts
Wang Z, Hegazy T, Long Z, et al. (2015) Noise-robust detection and tracking of salt domes in postmigrated volumes using texture, tensors, and subspace learning Geophysics. 80: WD101-WD116
Long Z, Alregib G. (2015) Saliency detection for videos using 3D FFT local spectra Proceedings of Spie - the International Society For Optical Engineering. 9394
Long Z, Wei W, Turlapaty A, et al. (2013) Fusion of Radiation and Electromagnetic Induction Data for Buried Radioactive Target Detection and Characterization Ieee Transactions On Nuclear Science. 60: 1126-1133
Long Z, Du Q, Younan NH. (2013) Multiscale spectral-spatial classification for hyperspectral imagery International Geoscience and Remote Sensing Symposium (Igarss). 1051-1054
Long Z, Younan NH. (2013) Multiscale texture segmentation via a contourlet contextual hidden Markov model Digital Signal Processing: a Review Journal. 23: 859-869
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