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Visual Computing and Image Processing Lab
Oklahoma State University
Imaging, Processing, nferencing and Learning

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Tracking/recognitionSegmentation/recognition Human motion estimationVideo segmentationImage segmentationSports video mining Statistical image modelingImage processingRetinal image processingRemote sensing analysis

Publications

Tracking and recognition

• J. Gong, G. Fan, J. P. Havlicek, N. Fan and D. Chen, “Infrared Target Tracking, Recognition and Segmentation using Shape-aware Level Set”, in Proc. IEEE International Conference on Image Processing (ICIP), Sept. 15-18, 2013, Melbourne, Australia.
• L. Yu, G. Fan, J. Gong, and J. P. Havlicek, “Simultaneous Target Recognition, Segmentation and Pose Estimation”, in Proc. IEEE International Conference on Image Processing (ICIP), Sept. 15-18, 2013, Melbourne, Australia.
• J. Gong, G. Fan, L. Yu, J. P. Havlicek, D. Chen and N. Fan, “Joint View-Identity Manifold for Infrared Target Tracking and Recognition”, accepted by Computer Vision and Image Understanding (CVIU), to appear in 2014.
• V. Venkataraman, G. Fan, J.P. Havlicek, X. Fan, Y. Zhai, and M. Yeary, "Adaptive Kalman Filtering for Histogram-based Appearance Learning in Infrared Imagery", IEEE Trans. on Image Processing, Vol. 21, Nov. 11, Nov. 2012, pages 4622-35.
• J. Gong, G. Fan, L. Yu, J. Havlicek and D. Chen, "Joint View-Identity Manifold for Target Tracking and Recognition", in Proc. IEEE International Conference on Image Processing (ICIP2012), Sept. 30-Oct. 3, 2012, Orlando, Florida.
• V. Venkataraman, G. Fan, L. Yu, X. Zhang, W. Liu, and J.P. Havlicek, “Automated Target Tracking and Recognition using Coupled View and Identity Manifolds for Shape Representation”, EURASIP Journal of Advances in Signal Processing (Special Issue on Object Tracking and Monitoring Using Advanced Signal Processing Techniques), 2011:124.
• V. Venkataraman, G. Fan, L. Yu, X. Zhang, W. Liu and J. P. Havlicek, "Joint Target Tracking and Recognition using View and Identity Manifolds", in Proc. of 8th IEEE International Workshop on Object Tracking and Classification in and Beyond Visible Spectrum (OTCBVS1011), in conjunction with CVPR11, Colorado Spring, Colorado, June 25, 2011.
• G. Fan, X. Fan, V. Venkataraman and Joseph Havlicek, "Appearance Learning by Adaptive Kalman Filters for Robust Infrared Tracking" (book chapter), Machine Vision Beyond Visible Spectrum,Springer-Verlag, Editors: Riad I. Hammoud, Guoliang Fan, Robert W. McMillan, Katsushi Ikeuchi, 2010 (to appear).
• G. Fan, X. Fan, V. Venkataraman, and Joseph Havlicek, "Vehicle tracking and recognition" (book chapter), Intelligent Video Surveillance: Systems and Technology (ISBN: 978-1-4398-1328-7), Taylor & Francis Group, Editors: Y. Ma and G. Qian, 2010.
• X. Fan, G. Fan and J. Havilcek, "Generative Graphical Models for Maneuvering Target Tracking", IEEE Trans. Aerospace and Electronics Systems, in press.
• C. Johnston, N. Mould, J. Havlicek and Guoliang Fan, "Dual Domain Auxiliary Particle Filter with Integrated Target Signature Update", in Proc. of 6th IEEE International Workshop on Object Tracking and Classification in and Beyond Visible Spectrum (OTCBVS09), in conjunction with CVPR09, Miami, Florida, 2009.
• V. Venkataraman, G. Fan, Xin Fan, and Joseph Havlicek, "Appearance Learning by Adaptive Kalman Filters for FLIR Tracking" in Proc. of 6th IEEE International Workshop on Object Tracking and Classification in and Beyond Visible Spectrum (OTCBVS09), in conjunction with CVPR09, Miami, Florida, 2009.
• V. Venkataraman, X. Fan and G. Fan, "Integrated Target Tracking and Recognition using Joint Appearance-Motion Generative Models", in Proc. of 5th IEEE International Workshop on Object Tracking and Classification in and Beyond Visible Spectrum (OTCBVS08), in conjunction with CVPR08, Anchorage, Alaska, 2008.
• Y. Zhai, M. Yeary, J. Havlicek, and G. Fan, "A New Centralized Sensor Fusion Tracking Methodology based on Particle Filtering for Power-aware Systems," IEEE Trans. Instrumentation and Measurement, Vol. 57, No. 10, pp2377-2387, Oct, 2008.
• X. Fan and G. Fan, "Generative Graphical Models for Maneuvering Objective Tracking and Dynamic Analysis", in Proc. of 4th IEEE International Workshop on Object Tracking and Classification in and Beyond Visible Spectrum (OTCBVS07), in conjunction with CVPR07, June 22, 2007.
• V.Venkataraman, G. Fan and X. Fan, "Target Tracking with Online Feature Selection in FLIR Imagery", in Proc. of 4th IEEE International Workshop on Object Tracking and Classification in and Beyond Visible Spectrum (OTCBVS07), in conjunction with CVPR07, June 22, 2007.
• G. Fan, V. Venkataraman, L. Tang, and J. Havlicek, "On Boosted and Adaptive Particle Filters for Affine-invariant Target Detection and Tracking", (book chapter) Lecture Note in Computer Science (LNCS), R. I. Hammoud and J. W. Davis (Editors), Springer-Verlag, 2008.
• G. Fan, V. Venkataraman, L. Tang, J. P. Havlicek, "A Comparative Study of Boosted and Adaptive Particle Filters for Affine-Invariant Target Detection and Tracking", in the Proc. of 3rd Joint IEEE International Workshop on Object Tracking and Classification in and Beyond the Visible Spectrum (OTCBVS'06) in conjunction with CVPR2006, New York City, June 22, 2006.
• J. P. Havlicek, C. T. Nguyen, G. Fan, and V. Venkataraman, "Integration of a Dual-band IR Data Acquisition System using Low-coast PV320 Camera", in Proc. SPIE Vol. 6206, Defense and Security Symposium, Infrared Technology and Applications XXXII, Orlando, FL, April 17-21, 2006.
• L. Tang, V.Venkataraman, and G, Fan, "Multi-aspect Target Tracking in Image Sequences Using Particle Filters", in Lecture Notes in Computer Science, Vol. 3804, Springer, also the Proc. of International Symposium on Visual Computing, Lake Tahoe, Nevada, Dec. 5-7, 2005.

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Segmentation and recognition

• C. Tian, G. Fan, X. Gao and Q. Tian, “Multi-view Face Recognition: From TensorFace to V-TensorFace and K-TensorFace”, IEEE Trans. on Systems, Man, and Cybernetics: Part B: Cybernetics, (Special issue on Subspace and Manifold Learning), Vol. 42, Issue 2, pages 320-333, April 2012.
• C. Chen and G. Fan, "Coupled Region-Edge Shape Priors for Joint Localization and Figure-ground Segmentation", Pattern Recognition, Vol. 43, Issue 7, July 2010, pp2521-2531.
• C. Chen and G. Fan, “Combining Spatial and Temporal Priors for Articulate Human Tracking with Online Learning”, in Proc. the 4th Dynamic Vision Workshop, in conjunction with ICCV09, Japan, Oct. 2009.
• X. Fan and G. Fan, "Graphical Models for Joint Segmentation and Recognition of License Plate Characters", IEEE Signal Processing Letters, Vol. 16, No. 1, pp10-13, Jan. 2009.
• C. Tian, G. Fan, and X. Gao, "Multi-view Face Recognition via Non-linear Tensor Decomposition", in Proc. International Conference on Pattern Recognition, Tampa, Florida, Dec. 2008.
• S. Jiang, K. Shuang, G. Fan, C. Tian, and Y. Wang, "Multiview Face Recognition based on Manifold Learning and Multilinear Analysis", in Proc. IEEE International Conference on Signal Processing, Oct. 26-29, 2008, Beijing, China.
• X. Fan and G. Fan, "Joint Segmentation and Recognition of License Plate Characters", in Proc. of IEEE International Conference on Image Processing (ICIP), San Antonio, TX, Sept. 2007.
• C. Chen and G. Fan, "Hybrid Body Representation for Integrated Pose Recognition, Localization and Segmentation", in Proc. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, Alaska, 2008.
• C. Cheng and G. Fan, "What can we learn from biological vision studies for human motion segmentation?", in the Proc. of International Symposium on Visual Computing, Lake Tahoe, Nevada, Nov. 6-8, 2006.

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Human motion estimation

• M. Ding and G. Fan, “Multi-Layer Joint Gait-Pose Manifold for Human Motion Modeling”, IEEE Automatic Face and Gesture Recognition (FG), April 22-26, 2013, Shanghai, China.
• X. Zhang, G. Fan and L. Chou, "Two-layer Dual Gait Generative Models for Human Motion Estimation from a Single Camera", Image and Vision Computing, (Special issue on Machine Learning in Motion Analysis), December 2012.
• M. Ding, G. Fan, X. Zhang, S. Ge, and L. Chou, "Structure-guided Manifold Learning for Video-based Motion Estimation", in Proc. IEEE International Conference on Image Processing (ICIP2012), Sept. 30-Oct. 3, 2012, Orlando, Florida.
• G. Fan and X. Zhang, “Gaussian Process-based Manifold Learning for Human Motion Modeling”, Intelligent Data Analysis for Real-Life Applications: Theory and Practice, Editors: R. Magdalena, M. Martínez, J.M. Martínez, P. Escandell and J. Vila, IGI Global, to appear, 2011.
• G. Fan, X. Zhang and M. Ding, “Gaussian Process for Human Motion Modeling: A Comparative Study”, in Proc. IEEE Workshop on Machine Learning for Signal Processing, Sept. 18-20, 2011, Beijing, China.
• X. Zhang and G. Fan, "Joint Gait-Pose Manifold for Video-based Human Motion Estimation", in Proc. the 3rd International Workshop on Machine Learning for Vision-based Motion Analysis (MLVMA’11), in conjunction with CVPR2011, Colorado Spring, Colorado, June 25, 2011.
• G. Fan and X. Zhang, "Video-based Human Motion Estimation by Part-whole Gait Manifold Learning", (book chapter), Machine Learning for Vision-based Motion Analysis, Editors: L. Wang, G. Zhao, L. Chen and M. Pietikaine, Springer, 2010 (to appear).
• X. Zhang, D. Biswas, and G. Fan, "A Software Pipeline for 3D Animation Generation using Mocap Data and Commercial Shape Models", in Proc. ACM Conference on Image and Video Retrieval, Xi'an, China, June 15-17, 2010.
• X. Zhang and G. Fan, "Dual Gait Generative Models for Human Motion Estimation from a Single Camera", IEEE Transactions on Systems, Man, and Cybernetics: Part B, Vol. 40, No. 4, pp1034-1049, Aug. 2010.
• X. Zhang, G. Fan, and L. Chou, “Two-layer Gait Generative Models for Estimating Unknown Human Gait Kinematics”, in Proc. the 2nd International Workshop on Machine Learning for Vision-based Motion Analysis (MLVMA’09), in conjunction with ICCV2009, Japan, Oct. 2009.
• X. Zhang and G. Fan, "Dual Generative Models for Human Motion Estimation from an Uncalibrated Monocular Camera", in Proc. International Conference on Pattern Recognition (ICPR), Tampa, Florida, Dec. 2008.

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Sports video mining

• G. Fan and Y. Ding, “Probabilistic Graphical Models for Sports Video Mining”, Intelligent Data Analysis for Real-Life Applications: Theory and Practice, Editors: R. Magdalena, M. Martínez, J.M. Martínez, P. Escandell and J. Vila, IGI Global, to appear, 2011.
• Y. Ding and G. Fan, “Finding the Game Flow from Sports Video”, in Proc. Joint ACM Workshop on Modeling and Representing Events (J-MRE'11), Nov. 30, 2011, Scottsdale, Arizona.
• G. Fan and Y. Ding, "Event Detection in Sports Video based on Generative-Discriminative Models" (book chapter), Computer Vision for Multimedia Applications: Methods and Solutions, Editors: J. Wang, J. Chen and S. Jiang, IGI, 2010.
• Y. Ding and G. Fan, "Event Detection in Sports Video based on Generative-Discriminative Models", in Proc. the 1st ACM International Workshop on
  Events in Multimedia (EiMM09) in conjunction with the ACM Multimedia Conference, Oct. 2009, Beijing, China.
• Y. Ding and G. Fan, "Sports Video Mining via Multi-channel Segmental Hidden Markov Models", IEEE Trans. on Multimedia, Vol. 11, No. 7, pp1301-1309, Nov. 2009.
• G. Fan and Y. Ding, "Statistical Machine Learning Approaches for Sports Video Mining using Hidden Markov Models" (book chapter), Handbook of Research on Machine Learning Applications (ISBN10: 1605667668), IGI Global, 2009.
• Y. Ding and G. Fan, "Multi-channel Segmental Hidden Markov Models for Sports Video Mining", in Proc. ACM Multimedia Conference, Oct. 27-Nov. 1 , 2008, Vancouver, Canada.
• Y. Ding and G. Fan, "Segmental Hidden Markov Models for View-based Sport Video Analysis", in Proc. of International Workshop on Semantic Learning Applications in Multimedia (SLAM07), in conjunction with CVPR07, Minneapolis, MN, June 22, 2007.
• Y. Ding and G. Fan, "Two-layer Generative Models for Video Mining", in Proc. of IEEE International Conference on Multimedia and Expo (ICME), Beijing, China, July 2007.
• Y. Ding and G. Fan, “Camera View Based American Football Video Analysis”, in IEEE Proc. International Symposium on Multimedia, San Diego, CA, Dec. 11-13.

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Video segmentation

• X. Song and G. Fan, "Selecting Salient Frames for Spatiotemporal Video Modeling and Segmentation", IEEE Trans. Image Processing, Vol. 16, No. 12, Dec. 2007.
• X. Song and G. Fan, "Joint Key-frame Extraction and Object Segmentation for Content-based Video Analysis", IEEE Trans. Circuits and Systems for Video Technology, Vol. 16, No. 7, pp904- 914, July 2006.
• X. Song and G. Fan, "A New Video Analysis Approach for Coherent Key-frame Extraction and Object Segmentation", in Proc. of the IEEE International Workshop on Multimedia Signal Processing, Shanghai, China, Oct. 30-Nov. 2, 2005.
• C. Chen and G. Fan, "Perception Principles Guided Video Segmentation", in Proc. of the IEEE International Workshop on Multimedia Signal Processing, Shanghai, China, Oct. 30-Nov. 2, 2005.
• X. Song and G. Fan, "Key-frame Extraction for Object-based Video Segmentation", in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2005), Philadelphia, PA, March 2005.
• X. Song and G. Fan, "Joint Key-frame Extraction and Object-based Video Segmentation", in Proc. of IEEE Workshop on Motion and Video Computing (MOTION 2005), Breckenridge, Colorado, Jan. 5-6, 2005.
• L. Liu and G. Fan, "Combined Key-frame Extraction and Object-based Video Segmentation", IEEE Trans. Circuits and System for Video Technology, July, 2005.

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Image segmentation

• X. Song and G. Fan, "On Capturing Likelihood Disparity for Unsupervised Image Segmentation", in Proc. IEEE Statistical Signal Processing Workshop, St. Louis, MO, September 2003.
• X. Song and G. Fan, "Unsupervised Bayesian Image Segmentation using Wavelet-domain Hidden Markov Models", in Proc. IEEE International Conference on Image Processing, Barcelona, Span, September 2003.
• X. Song and G. Fan, "Unsupervised Image Segmentation using Wavelet-domain Hidden Markov Models", in Proc. SPIE Wavelet X, Volume 5207, San Diego, CA, August 2003.
• L. Liu, Y. Dong, X. Song, and G. Fan, "A Entropy-based Segmentation Algorithm for Computer-Generated Document Images", in Proc. IEEE International Conference on Image Processing, Barcelona, Span, September 2003.
• Y. Dong, L. Liu, X. Song, and G. Fan, "A New Simplified Quantization Rate-Distortion Model for Fast Document Image Segmentation", in Proc. of the 45th IEEE International Midwest Symposium on Circuits and Systems, Tulsa, OK, Aug. 2002.
• X. Song and G. Fan, "A Study of Supervised, Semi-Supervised and Unsupervised Multiscale Bayesian Image Segmentation", in Proc. of the 45th IEEE International Midwest Symposium on Circuits and Systems, Tulsa, OK, Aug. 2002.
• G. Fan and X. Song, "A Study of Contextual Modeling and Texture Characterization for Multiscale Bayesian Segmentation", in Proc. of the IEEE International Conference on Image Processing (ICIP2002), Rochester, NY, Sept. 2002.
• G. Fan and X.-G. Xia, "On Context-Based Bayesian Image Segmentation: Joint Multi-context and Multiscale Approach and Wavelet-Domain Hidden Markov Models", in Proc. of the 35th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 4-7, 2001 (Invited paper).
• G. Fan and X.-G. Xia, "A Joint Multi-context and Multiscale Approach to Bayesian Image Segmentation", IEEE Tran. on Geoscience and Remote Sensing, Vol 39, No. 12, pp2680 -2688, Dec. 2001.
• G. Fan and X.-G. Xia, "Multiscale Texture Segmentation Using Hybrid Contextual Labeling Tree", in Proc. of the IEEE International Conference on Image Processing (ICIP2000), Vancouver, Canada, Sept. 2000.

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Statistical image modeling

• G. Fan and X.-G. Xia, "Statistical Image Modeling and Processing Using Wavelet-Domain Hidden Markov Models", (book chapter) Nonlinear Signal and Image Processing: Theory, Methods, and Applications, K. E. Barner and G. R. Arce (Editors), CRC Press, 2003.
• G. Fan and X.-G. Xia, "Wavelet-based Texture Analysis and Synthesis Using Hidden Markov Models", IEEE Trans. Circuits and Systems, Part I, Vol. 50, No. 1, pp106-120, Jan. 2003 (corrections).
• G. Fan, "Wavelet-Domain Statistical Image Modeling and Processing", Ph.D. dissertation, University of Delaware, Summer 2001.
• G. Fan and X.-G. Xia, "Image Denoising Using Local Contextual Hidden Markov Model in the Wavelet Domain", IEEE Signal Processing Letter, Vol. 8, No. 5, May 2001, pp125-128.
• G. Fan and X.-G. Xia, "Improved Hidden Markov Models in the Wavelet-Domain", IEEE Trans. on Signal Processing, Vol. 49, No. 1 Jan. 2001, pp115-120.
• G. Fan and X.-G. Xia, "Wavelet-Based Statistical Image Processing Using Hidden Markov Tree Model", in Proc. of the 2000 Conference on Information Science and Systems (CISS2000), Princeton, NJ, March, 2000, ppTA5-31-TA-5-36.
• G. Fan and X.-G. Xia, "Wavelet-Based Image Denoising Using Hidden Markov Models", in Proc. of the IEEE International Conference on Image Processing (ICIP2000), Vancouver, Canada, Sept. 2000.
• G. Fan and X.-G. Xia, "Texture Analysis and Synthesis Using Wavelet-Domain Hidden Markov Models", in Proc. of the 5th IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, Baltimore, MD, June 2001.
• G. Fan and X.-G. Xia, "Maximum Likelihood Texture Analysis and Classification Using Wavelet-Domain Hidden Markov Models", in Proc. of the 34th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Oct. 29-Nov. 1, 2000.

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Image processing

• J. Sun, G. Fan, X. Wu, “New Local Edge Binary Patterns for Image Retrieval”, in Proc. IEEE International Conference on Image Processing (ICIP), Sept. 15-18, 2013, Melbourne, Australia.
• Z. Zhou and G. Fan, “A Directional Shock Diffusion Approach to Single Image Super-resolution”, in Proc. IEEE International Conference on Image Processing (ICIP), Sept. 15-18, 2013, Melbourne, Australia.
• L. Liu and G. Fan, "A New JPEG2000 Region-of-Interest Image Coding Method: Partial Significant Bitplanes Shift", IEEE Signal Processing Letter, Vol. 10, No. 2, pp35-39, Feb. 2003.
• L. Liu and G. Fan, "A New Method for JPEG2000 Region-of-Interest Image Coding: Most Significant Bitplanes Shift", in Proc. of the 45th IEEE International Midwest Symposium on Circuits and Systems, Tulsa, OK, Aug. 2002.
• G. Fan and W. K. Cham, "Model-Based Edge Reconstruction for Low Bit-rate Wavelet Compressed Images", IEEE Trans. on Circuits and Systems for Video Technology, Vol. 10, No. 1, 2000, pp120-132.
• G. Fan and W. K. Cham, "Post-processing of Low Bit-rate Wavelet-based Image Coding Using Multiscale Edge Characterization", IEEE Trans. on Circuits and Systems for Video Technology, Vol. 11, No. 12, pp1263 -1272, Dec. 2001.
• G. L. Fan, W. K. Cham and J. Z. Liu, "Model-Based Edge Reconstruction for Low Bit-rate Wavelet Image Coding", in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP98), Seattle, WA, 1998, p2561-2564.
• G. L. Fan and W. K. Cham, "Multiscale Image Reconstruction for Low Bit-Rate Wavelet Image Coding", in Proc. of the 1998 IEEE International Conference on Image Processing (ICIP98), Chicago, IL, Oct. 1998, p420-424.
• G. Fan and L. Zhou, "Visual Entropy -based Classified Bath Fractal Transform for Image Coding", in Proc. of the IEEE International Conference on Signal Processing (ICSP1996), Oct., 1996, Beijing, China.

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Retinal image processing

• T. Chanwimaluang, G. Fan, IEEE, G. G. Yen, and S. R. Fransen, "3-D Retinal Curvature Estimation",IEEE Trans. on Information Technology in Biomedicine, Vol. 13, No. 6, pp997-1005, Nov. 2009.

• T. Chanwimaluang and G. Fan, "Constrained Optimization for Retinal Curvature Estimation Using an Affine Camera" in the Proc. of International Workshop on Beyond Multiview Geometry: Robust Estimation and Organization of Shapes from Multiple Cues (BMG07), in conjunction with CVPR2007, Minneapolis, Minnesota, June 22, 2007.
• T. Chanwimaluang and G. Fan, "Affine Camera for 3D Retinal Surface Reconstruction" in the Proc. of International Symposium on Visual Computing, Lake Tahoe, Nevada, Nov. 6-8, 2006.
• Xin Zhang and G. Fan, "Retinal Spot Lesion Detection Using Adaptive Multiscale Morphological Processing" in the Proc. of International Symposium on Visual Computing, Lake Tahoe, Nevada, Nov. 6-8, 2006.
• T. Chanwimaluang and G. Fan, "Retinal Image Registration for NIH's ETDRS", in Lecture Notes in Computer Science, Vol. 3804, Springer, also the Proc. of International Symposium on Visual Computing, Lake Tahoe, Nevada, Dec. 5-7, 2005.
• T. Chanwimaluang, G. Fan, and S. Fransen, "Hybrid Retinal Image Registration", IEEE Trans. on Information Technology in Biomedicine, Vol. 10, No. 1, pp129-142, Jan. 2006. (demos)
• A. Awawedeh and G. Fan, "Pseudo Cepstrum for Assessing Stereo Quality of Retinal Images", in Proc. of the 37th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 2003.
• T. Chanwimaluang and G. Fan, "An Efficient Algorithm for Extraction of Anatomical Structures in Retinal Images", in Proc. IEEE International Conference on Image Processing, Barcelona, Span, September 2003.
• T. Chanwimaluang and G. Fan, "An Efficient Blood Vessel Detection Algorithm for Retinal Images using Local Entropy Thresholding", in Proc. of the 2003 IEEE International Symposium on Circuits and Systems, Bangkok, Thailand, May 25-28, 2003.

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Remote sensing analysis

• X. Song, G. Fan and R. Mahesh, "SVM-based Enhanced One-class Classification for Remotely Sensed Imagery", IEEE Geoscience and Remote Sensing Letters, April 2008.
• R. Mahesh, G. Fan and J. Thomas, et. al., "A Web-based GIS Decision Support System for Managing and Planning USDA's Conservation Reserve Program (CRP)", Environmental Modelling and Software, Vol. 22, No. 9, pp1270-1280, Sept. 2007.
• X. Song and G. Fan, "A $\nu$-insensitive SVM Approach for Compliance Monitoring of the Conservation Reserve Program", IEEE Geoscience and Remote Sensing Letters, April, 2005.
• G. Cherian, X. Song, G. Fan, and M. Rao, "Application of Support Vector Machines for Automatic Compliance Monitoring of the Conservation Reserve Program (CRP) Tracts", in Proc. IEEE Goescience and Remote Sensing Symposium (IGARSS2004), Alaska, September 20-24, 2004.
• X. Song and G. Fan, "Automated CRP Mapping using Non-parametric Machine Learning Approaches", IEEE Trans. on Geoscience and Remote Sensing, April, 2005.
• X. Song, G. Fan, and M. Rao, "Machine Learning Approaches for Multisource Geospatial Data Classification with Application to CRP Mapping in Texas County, Oklahoma", in Proc. IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, NASA Goddard Visitor Center, Washington DC, October 27/28, 2003.

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Copyright © 2008 VCIPL@OSU, All rights reserved.
(Acknowledgements: The template is from Interspire Free Templates, and free pictures are from 3DLuVr.com.)

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