S. Prasad, L.M. Bruce, J. Chanussot (Editors), Optical Remote Sensing – Advances in Signal Processing and Exploitation Techniques, Springer Verlag, Berlin, March 2011. (ISBN: 978-3-642-14211-6)
S. Prasad, L.M. Bruce, J. Chanussot, “Introduction – Signal Processing and Exploitation for Optical Remote Sensing,” Chapter 1 in Optical Remote Sensing – Advances in Signal Processing and Exploitation Techniques, Springer Verlag, Berlin, March 2011. (ISBN: 978-3-642-14211-6)
S. Prasad, L.M. Bruce, “A Divide-and-Conquer Paradigm for Hyperspectral Classification and Target Recognition,” Chapter 7 in Optical Remote Sensing – Advances in Signal Processing and Exploitation Techniques, Springer Verlag, Berlin, March 2011. (ISBN: 978-3-642-14211-6)
S. Prasad, L.M. Bruce, J.E. Ball, “Information Fusion in a High Dimensional Feature Space for Robust Computer Aided Diagnosis using Digital Mammograms,” Chapter 9 in New Developments in Biomedical Engineering, Edited by: D. Campolo, In-Tech Publishers, Croatia, January 2010. (ISBN: 978-953-7619-57-2)
Peer Reviewed Journal Publications
N. Makkar, L. Yang and S. Prasad, “Adversarial Learning Based Discriminative Domain Adaptation for Geospatial Image Analysis,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 150-162, 2022, doi: 10.1109/JSTARS.2021.3132259.
R. Mankar, C. Gajjela, F. Shahraki, S. Prasad, D. Mayerich, R. Reddy, “Multi-modal image sharpening in fourier transform infrared (FTIR) microscopy,” Analyst, 146(15), pp 4822-4834, 2021
K. Safari, S. Prasad and D. Labate, “A Multiscale Deep Learning Approach for High-Resolution Hyperspectral Image Classification,” in IEEE Geoscience and Remote Sensing Letters, vol. 18, no. 1, pp. 167-171, Jan. 2021, doi: 10.1109/LGRS.2020.2966987.
S. Mukherjee, S. Prasad. “A spatial–spectral semisupervised deep learning framework using siamese networks and angular loss.” Computer Vision and Image Understanding 194 (2020): 102943.
Y Xu, B Du, L Zhang, D Cerra, M Pato, E Carmona, S Prasad, N Yokoya, et al “Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 12, no. 6, pp. 1709-1724, June 2019, doi: 10.1109/JSTARS.2019.2911113.
B. Le Saux, N. Yokoya, R. Hänsch and S. Prasad, “Advanced Multisource Optical Remote Sensing for Urban Land Use and Land Cover Classification [Technical Committees],” in IEEE Geoscience and Remote Sensing Magazine, vol. 6, no. 4, pp. 85-89, Dec. 2018
L. Yan, M. Cui and S. Prasad, “Joint Euclidean and Angular Distance-Based Embeddings for Multisource Image Analysis,” in IEEE Geoscience and Remote Sensing Letters, vol. 15, no. 7, pp. 1110-1114, July 2018, doi: 10.1109/LGRS.2018.2827845.
X. Zhou and S. Prasad, “Deep Feature Alignment Neural Networks for Domain Adaptation of Hyperspectral Data,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 10, pp. 5863-5872, Oct. 2018, doi: 10.1109/TGRS.2018.2827308.
S. Prasad, W. Liao, M. He, J. Chanussot, “Foreword to the Special Issue on Hyperspectral Remote Sensing and Imaging Spectroscopy,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 4, April 2018
S. Mukherjee, M. Cui and S. Prasad, “Spatially Constrained Semisupervised Local Angular Discriminant Analysis for Hyperspectral Images,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 4, pp. 1203-1212, April 2018
H. Wu and S. Prasad, “Semi-Supervised Deep Learning Using Pseudo Labels for Hyperspectral Image Classification,” in IEEE Transactions on Image Processing, vol. 27, no. 3, pp. 1259-1270, March 2018
H. Wu, S. Prasad. “Semi-supervised dimensionality reduction of hyperspectral imagery using pseudo-labels.” Pattern Recognition 74 (2018): 212-224.
R. Mankar, M. J. Walsh, R. Bhargava, S. Prasad, & D. Mayerich, “Selecting optimal features from Fourier transform infrared spectroscopy for discrete-frequency imaging”, Analyst, 143(5), 1147-1156.
X. Zhou and S. Prasad, “Domain Adaptation for Robust Classification of Disparate Hyperspectral Images,” in IEEE Transactions on Computational Imaging, vol. 3, no. 4, pp. 822-836, Dec. 2017
X. Zhou and S. Prasad, “Active and Semisupervised Learning With Morphological Component Analysis for Hyperspectral Image Classification,” in IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 8, pp. 1348-1352, Aug. 2017
S. Prasad, D. Labate, M. Cui, Y. Zhang, “Morphologically Decoupled Structured Sparsity for Rotation-Invariant Hyperspectral Image Analysis,” in the IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 8, pp. 4355-4366, Aug. 2017 (*Featured on Journal Cover).
H. Wu, S. Prasad, “Semi-supervised Deep Learning using Pseudo Labels for Hyperspectral Image Classification,” in the IEEE Transactions on Image Processing, vol. 27, No. 3, pp 1259 – 1270, March 2018.
X. Zhou and S. Prasad, “Deep Feature Alignment Neural Networks for Domain Adaptation of Hyperspectral Data,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 10, pp. 5863-5872, Oct. 2018.
H. Wu, S. Prasad, “Semi-Supervised Dimensionality Reduction of Hyperspectral Imagery using Pseudo-Labels,” Pattern Recognition, Vol. 74, pp 212-224, February 2018.
X. Zhou, S. Prasad, “Domain Adaptation for Robust Classification of Disparate Hyperspectral Images,” in the IEEE Transactions on Computational Imaging, Vol. 3, No.5, pp 822 – 836, December 2017.
X. Zhou and S. Prasad, “Active and Semisupervised Learning With Morphological Component Analysis for Hyperspectral Image Classification,” in IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 8, pp. 1348-1352, Aug. 2017.
Y. Zhang, S. Prasad, A. Kilicarslan, J. L. Contreras-Vidal, “Multiple Kernel Based Region Importance Learning for Neural Classification of Gait States from EEG Signals,” in Frontiers in neuroscience, April 2017.
H. Wu, S. Prasad, “Convolutional Recurrent Neural Networks for Hyperspectral Data Classification,” in Remote Sensing, Vol. 9, No. 3, March 2017.
M. Cui, S. Prasad, “Sparse Representation-Based Classification: Orthogonal Least Squares or Orthogonal Matching Pursuit?“, in Pattern Recognition Letters, Vol. 84, pp 120-126, Dec. 2016.
J. Guo, X. Zhou, J. Li, A. Plaza and S. Prasad, “Superpixel-Based Active Learning and Online Feature Importance Learning for Hyperspectral Image Analysis,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 1, pp. 347-359, Jan. 2017.
Y. Zhang, S. Prasad, “Multisource Geospatial Data Fusion via Local Joint Sparse Representation,” in the IEEE Transactions on Geoscience and Remote Sensing, Vol. 54, No. 6, pp. 3265-3276, June 2016.
X. Zhou, S. Prasad, “Wavelet-Domain Multiview Active Learning for Spatial-Spectral Hyperspectral Image Classification,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 2016.
H. Wu, S. Prasad, “Dirichlet Process Based Active Learning and Discovery of Unknown Classes for Hyperspectral Image Classification,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 8, pp. 4882-4895, Aug. 2016.
M. Dalla Mura, S. Prasad, F. Pacifici, P. Gamba, J. Chanussot and J. A. Benediktsson, “Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing,” in Proceedings of the IEEE, vol. 103, no. 9, pp. 1585-1601, Sept. 2015.
M. Cui, S. Prasad, “Angular Discriminant Analysis for Hyperspectral Image Classification“, in IEEE Journal of Selected Topics in Signal Processing, Vol. 9, No. 6, pp. 1003-1015, Sept. 2015.
M. Cui, S. Prasad, “Class-Dependent Sparse Representation Classifier for Robust Hyperspectral Image Classification“, in IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp 2683-2695, May 2015.
T. Priya, S. Prasad, H. Wu, “Superpixels for Spatially Reinforced Bayesian Classification of Hyperspectral Images,” in the IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 5, pp 1071-1075, January 2015.
Y. Zhang, H. Yang, S. Prasad, E. Pasolli, J. Jung, M. Crawford, “Ensemble Multiple Kernel Active Learning For Classification of Multisource Remote Sensing Data“, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 2, pp 845-858, February 2015.
Y. Zhang, S. Prasad, “Locality Preserving Composite Kernel Feature Extraction for Multi-Source Geospatial Image Analysis,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 3, pp 1385-1392, March 2015.
T. C. Bulea, S. Prasad, A. Kilicarslan, J. L. Contreras-Vidal, “Sitting and standing intention can be decoded from scalp EEG recorded prior to movement execution,” in Frontiers in neuroscience, 8, November 2014.
J. Jung, E. Pasolli, S. Prasad, J. Tilton, M. Crawford, “A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 7, No. 2, pp 491-502, February 2014.
D. Lunga, S. Prasad, M. Crawford, O. Ersoy, “Manifold-Learning-Based Feature Extraction for Classification of Hyperspectral Data,” in the IEEE Signal Processing Magazine, Vol. 31, No. 1, pp 55-66, January 2014.
S. Prasad, M. Cui, W. Li, J. E. Fowler, “Segmented Mixture-of-Gaussian Classification for Hyperspectral Image Analysis,” in the IEEE Geoscience and Remote Sensing Letters, Volume 11, No. 1, pp 138-142, January 2014.
W. Li, S. Prasad, J. E. Fowler, “Hyperspectral Image Classification Using Gaussian Mixture Models and Markov Random Fields,” in the IEEE Geoscience and Remote Sensing Letters, Vol. 11, No. 1, 153 – 157, January 2014.
Z. Ye, S. Prasad, W. Li, J. E. Fowler, M. He, “Classification Based on 3-D DWT and Decision Fusion for Hyperspectral Image Analysis,” in the IEEE Geoscience and Remote Sensing Letters, Vol. 11, No. 1, pp 173-177, January 2014.
W. Li, S. Prasad, J. E. Fowler, “Integration of Spectral-Spatial Information for Hyperspectral Image Reconstruction from Compressive Random Projections,” in the IEEE Geoscience and Remote Sensing Letters, Vol 10, No. 6, pp 1379 – 1383, November 2013.
S. Samiappan, S. Prasad, L. Bruce, “Non-Uniform Random Feature Selection and Kernel Density Scoring with SVM based Ensemble Classification for Hyperspectral Image Analysis,” in the IEEE Journal on Selected Topics in Applied Earth Observations and Remote Sensing, Vol 6, No. 2, pp 792 – 800, April 2013.
W. Li, S. Prasad, J. E. Fowler, “Noise-Adjusted Subspace Discriminant Analysis for Hyperspectral-Image Classification” in the IEEE Geoscience and Remote Sensing Letters, Vol 10, No. 6, pp 1374-1378, November 2013.
W. Li, S. Prasad, J. E. Fowler “Classification and Reconstructions from Random Projections for Hyperspectral Image Analysis” in the IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, No. 2, pp 833-843, February 2013.
S. Prasad, W. Li, J. E. Fowler, L.M. Bruce “Information Fusion in the Redundant Wavelet Transform Domain for Noise Robust Hyperspectral Classification” in the IEEE Transactions on Geoscience and Remote Sensing, Vol 50, No. 9, pp 3474-3486, September 2012.
M. Cui, S. Prasad, M. Mahrooghy, J. Aanstoos, M.A. Lee, L.M. Bruce “Decision Fusion of Textural Features Derived from Polarimetric Data for Levee Assessment” in the IEEE Journal on Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 5, No. 3, pp 970-976, June 2012.
W. Li, S. Prasad, J. E. Fowler, L.M. Bruce “Locality Preserving Dimensionality Reduction and Classification for Hyperspectral Image Analysis” in the IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 4, pp 1185-1198, April 2012.
W. Li, S. Prasad, J. E. Fowler, and L. M. Bruce, “Locality-Preserving Discriminant Analysis in Kernel-Induced Feature Spaces for Hyperspectral Image Classification,” in IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 5, pp 895-898, September 2011.
H.Kalluri, S. Prasad, L.M. Bruce “Decision Level Fusion of Spectral Reflectance and Derivative Information for Robust Hyperspectral Land Cover Classification,” in the IEEE Transactions on Geoscience and Remote Sensing, vol.48, no.11, pp.4047-4058, November, 2010.
S. Prasad, L.M. Bruce “Information Fusion in Kernel Induced Spaces for Robust Sub-Pixel Hyperspectral ATR,” in the IEEE Geoscience and Remote Sensing Letters – Vol. 6 no. 3 – pp 572-576, July, 2009.
G. Licciardi, F. Pacifici, D. Tuia, S. Prasad, T. West, F. Giacco, C. Thiel, J. Inglada, E. Christophe, J. Chanussot, P. Gamba, “Decision Fusion for the Classification of Hyperspectral Data: Outcome of the 2008 GRS-S Data Fusion Contest,” in the IEEE Transactions on Geoscience and Remote Sensing – Vol. 47 no. 11 – pp 3857-3865, November, 2009.
S. Prasad, L.M. Bruce, “Decision Fusion with Confidence-based Weight Assignment for Hyperspectral Target Recognition,” in the IEEE Transactions on Geoscience and Remote Sensing, vol. 46, No. 5, May 2008.
S. Prasad, L.M. Bruce, “Limitations of Principal Components Analysis for Hyperspectral Target Recognition,” in the IEEE Geoscience and Remote Sensing Letters, Vol. 5, Issue 4, pp 625-629, October 2008.
Peer Reviewed Conference Publications
Y. Zhang, H.L. Yang, D. Lunga, S. Prasad, M. Crawford, “Context Dependent Manifold Learning for Hyperspectral Image Classification,” in Proceedings of the 2014 Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 25-27 June, Lausanne, Switzerland, 2014
X. Zhou, S. Prasad, and M. M. Crawford, “Wavelet domain multi-view active learning for hyperspectral image analysis”, in Proceedings of the 2014 IEEE Workshop on Hyperspectral Image and Signal Process.: Evolution in Remote Sensing (WHISPERS), 25-27 June, Lausanne, Switzerland, 2014.
X. Zhou, S. Prasad, and M. M. Crawford, “Wavelet domain active learning for robust classification of full-waveform LiDAR data.” in Proceedings of the 2014 IEEE International Geosciences and Remote Sensing Symposium (IGARSS), pp. 3566-3569,Quebec, Canada, July 13-18, 2014.
M. Cui, S. Prasad. “Sparsity promoting dimensionality reduction for classification of high dimensional hyperspectral images.” in Proceedings of the IEEE Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 2154 – 2158, Vancouver, Canada, 2013.
M. Cui, S. Prasad, “Multi-Scale Sparse Representation Classification for Robust Hyperspectral Image Analysis,” in proceedings of the 1’st IEEE Global Conference on Signal and Image Processing (GlobalSIP) on New Sensing and Inference Methods, pp. 969-972, December 2013.
H. Wu, S. Prasad, “Infinite Gaussian Mixture Models for Robust Decision Fusion of Hyperspectral Imagery and Full Waveform LiDAR Data,” in proceedings of the 1’st IEEE Global Conference on Signal and Image Processing (GlobalSIP) on New Sensing and Inference Methods, pp 1025 – 1028, December 2013.
S. Prasad, M. Cui, “Sparse Representations for Classification of High Dimensional Multi-Sensor Geospatial Data,” in proceedings of the 47’th IEEE Asilomar Conference on Signals, Systems and Computers, November 2013.
H. H. Yang, Y. Zhang, S. Prasad, M.M. Crawford, “Multi-Kernel active learning for robust geo-spatial image analysis,” in Proceedings of the 2013 IEEE Geoscience and Remote Sensing Symposium, Melbourne, Australia, July 22-26, 2013.
M. Cui, S. Prasad, L. M. Bruce, R. Shrestha, “Robust Spatial-Spectral Hyperspectral Image Classification for Vegetation Stress Detection,” in proceedings of the IEEE Geosciences and Remote Sensing Symposium, Munich, Germany, 2012.
M. Lee, L. Bruce, J. Aanstoos, S. Prasad, “Application of Omni-Directional Texture Analysis to SAR Images for Levee Landslide Detection,” in proceedings of the IEEE Geosciences and Remote Sensing Symposium, Munich, Germany, 2012.
W. Li, S. Prasad, J. Fowler, M. Cui, “Locality Preserving Nonnegative Matrix Factorization for Hyperspectral Image Classification,” in proceedings of the IEEE Geosciences and Remote Sensing Symposium, Munich, Germany, 2012.
W. Li, S. Prasad, J. Fowler, M. Cui, “Locality-Preserving Discriminant Analysis for Hyperspectral Image Classification Using Local Spatial Information,” in proceedings of the IEEE Geosciences and Remote Sensing Symposium, Munich, Germany, 2012.
W. Li, S. Prasad, Z. Ye, J. Fowler, Q. Du, “Noise-Adjusted Subspace Linear Discriminant Analysis for Hyperspectral Image Classification,” in proceedings of the 3’d IEEE Workshop on Hyperspectral Signal and Image Processing: Evolution in Remote Sensing, Shanghai, China, 2012.
Z. Ye, S. Prasad, W. Li, J. Fowler, M. He, “Locality-Preserving Discriminant Analysis and Gaussian Mixture Models for Spectral-Spatial Classification of Hyperspectral Imagery,” in proceedings of the 3’d IEEE Workshop on Hyperspectral Signal and Image Processing: Evolution in Remote Sensing, Shanghai, China, 2012.
W. Li, S. Prasad, J. Fowler, L.M. Bruce, “Class Dependent Compressive-Projection Principal Component Analysis for Hyperspectral Image Reconstruction,” in proceedings of the 3’d IEEE Workshop on Hyperspectral Signal and Image Processing: Evolution in Remote Sensing, 2011.
W. Li, S. Prasad, J. Fowler, L.M. Bruce, “A Multi-Modal Pattern Classification Framework for Hyperspectral Image Analysis,” in proceedings of the 3’d IEEE Workshop on Hyperspectral Signal and Image Processing: Evolution in Remote Sensing, 2011.
M.A. Lee, L.M. Bruce, S. Prasad, “Concurrent Spatial-Spectral Band Grouping: Providing a Spatial Context for Spectral Band Grouping,” in proceedings of the 3’d IEEE Workshop on Hyperspectral Signal and Image Processing: Evolution in Remote Sensing, 2011.
S. Samiappan, S. Prasad, L.M. Bruce, E. Hansen “Branch and Bound based Feature Elimination for Support Vector Machine based Classification of Hyperspectral Images,” in proceedings of theIEEE Geoscience and Remote Sensing Symposium, 2011.
S. Samiappan, S. Prasad, L.M. Bruce, “Automated Hyperspectral Imagery Analysis via Support Vector Machines based Multi-Classier System with Non-Uniform Random Feature Selection,” in proceedings of the Geoscience and Remote Sensing Symposium, 2011.
M. Cui, S. Prasad, M. Mahrooghy, L.M. Bruce, J. Aanstoos, “Genetic Algorithms and Linear Discriminant Analysis based Dimensionality Reduction for Remotely Sensed Image Analysis,” in proceedings of the Geoscience and Remote Sensing Symposium, 2011.
H. Kalluri, S. Prasad, L.M. Bruce, S. Samiappan, “Data Dependant Adaptation for Improved Classification of Hyperspectral Imagery,” Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, 2010.
S. Samiappan, S. Prasad, and L.M. Bruce, “NASAs Upcoming HyspIRI Mission Precision Vegetation Mapping with Limited Ground Truth,” Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, 2010.
M. A. Lee, S. Prasad, L. M. Bruce, T. R. West, D. Reynolds, T. Irby, and H. Kalluri, “Sensitivity of Hyperspectral Classification Algorithms to Training Sample Size,” in proceedings of the IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Grenoble, France, 2009.
H. Kalluri, S. Prasad, L.M. Bruce, “Fusion of Spectral Reflectance and Derivative Information for Robust Hyperspectral Land Cover Classification,” in proceedings of the IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Grenoble, France, 2009.
S. Prasad, L.M. Bruce, J.E. Ball, “A Multi-classifier and Decision Fusion Framework for Robust Classification of Mammographic Masses,” in proceedings of IEEE Engineering in Medicine and Biology Conference, Vancouver, Canada, August 2008.
S. Prasad, L.M. Bruce, “Multiple Kernel Discriminant Analysis and Decision Fusion for Robust Sub-pixel Hyperspectral Target Recognition,” in the proceedings of the IEEE Geoscience and Remote Sensing Symposium, Boston, MA, July 2008. ( 2008 Mikio Takagi Student Prize Award for Best Student Paper )
S. Prasad, L.M. Bruce, “Overcoming the Small Sample Size Problem in Hyperspectral Classification and Detection Tasks,” in the proceedings of the IEEE Geoscience and Remote Sensing Symposium, Boston, MA, July 2008.
S. Prasad, L.M. Bruce, H. Kalluri “A Robust Multi-Classifier Decision Fusion Framework for Hyperspectral, Multi-Temporal Classification,” in the proceedings of the IEEE Geoscience and Remote Sensing Symposium, Boston, MA, July 2008.
T. West, L.M. Bruce, S. Prasad, “Wavelet Packet Tree Pruning Metrics for Hyperspectral Feature Extraction,” in the proceedings of the IEEE Geoscience and Remote Sensing Symposium, Boston, MA, July 2008.
S. Prasad, L.M. Bruce, “Hyperspectral Feature Space Partitioning via Mutual Information for Data Fusion ,” Proceedings of the IEEE Geoscience and Remote Sensing Symposium , Barcelona, Spain, July 2007.
S. Prasad, L.M. Bruce, “Limitations of Subspace LDA in Hyperspectral Target Recognition Applications,” Proceedings of the IEEE Geoscience and Remote Sensing Symposium , Barcelona, Spain, July 2007.
T. West, L.M. Bruce, S. Prasad, “Multiclassifiers and Decision Fusion in the Wavelet Domain for Exploitation of Hyperspectral Data,” Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Barcelona, Spain, July 2007.
J.E. Ball, L.M. Bruce, S. Prasad, T.R. West, “Level Set Hyperspectral Image Segmentation using Spectral Information Divergence (SID) based Best Band Selection,” Proceedings of the IEEE Geoscience and Remote Sensing Symposium , Barcelona, Spain, July 2007.
S. Prasad, L.M. Bruce, “Information Theoretic Partitioning and Confidence based Weight Assignment for Multi-Classifier Decision Level Fusion in Hyperspectral Target Recognition Applications,” Proceedings of the SPIE Defense and Security Symposium, Orlando, Florida, USA, April 2007.