"Segmentation and Learning in the Quantitative Analysis of Microscopy Images", Christy Ruggiero, Amy Ross, Reid Porter, Proceedings of SPIE, Image Processing: Machine Vision Applications VIII, 2014. [LA-UR-15-21115]
"Learning Watershed Cut Energy Functions", Reid Porter, Diane Oyen, Beate G. Zimmer, LANL Technical Report, 2015. [LA-UR-15-20316]
"Links Betweeen Binary Classification and the Assignment Problem in Ordered Hypothesis Machines", Reid Porter, Beate G. Zimmer, Proceedings of SPIE, Image Processing: Machine Vision Applications VIII, 2014. [LA-UR-14-26673]
"User-Driven Sampling Strategies in Image Exploitation", Harvey N., R. Porter, in Proceedings of SPIE 9017, Visualization and Data Analysis 2014. [LA-UR-13-29029]
"Investigation of Segmentation Based Pooling for Image Quantification", Porter, R., N. Harvey, C. Ruggiero, in Proceedings of SPIE 9024, Image Processing: Machine Vision Applications VII. 2014. [LA-UR-14-20361]
"Learning to Merge: A New Tool for Interactive Mapping", Porter, R., S. Lundquist, C. Ruggiero, in Proceedings of SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX. 2013. [LA-UR-13-22821]
"Interactive Machine Learning in Data Exploitation", Porter, R., J. Theiler, and D. Hush, Short Version: Computing in Science and Engineering 15:5 (Sept/Oct 2013) 12-30, Technical Report. 2013, Los Alamos National Lab. [LA-UR-13-20441]
"Information Space Models for Data Integration, and Entity Resolution", Porter, R., et al. in Proceedings of SPIE. 2012. [LA-UR-12-20601]
"Ordered Hypothesis Machines", Zimmer, B.G., D. Hush, and R. Porter, Journal of Mathematical Image and Vision, DOI:10.1007/s10851-011-0293-z, 2011. [LA-UR-10-06253]
"Interactive Image Quantification Tools for Nuclear Material Foreinsics", Porter, R. and C. Ruggiero. in Proceedings of SPIE. 2011. San Francisco. [LA-UR 11-00019]
"Error Minimizing Algorithms for Nearest Neighbor Classifiers", Porter, R., D. Hush, and B.G. Zimmer. in Proceedings of the SPIE. 2011. San Francisco. [LA-UR 11-00020]
"Faster and Better: A Machine Learning Approach to Corner Detection", Rosten, E., R. Porter, and T. Drummond, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2010. 32(1): p. 105-119. [LA-UR-07-3912]
"Toward Interactive Search in Remote Sensing Imagery", Porter, R., et al., in Proceedings of the SPIE. 2010. p. 77090V-77090V-10. [LA-UR-10-01385]
"Narrowing the Semantic Gap in Wide Area Motion Imagery", Porter, R., D. Hush, and A. Fraser, IEEE Signal Processing Magazine, 2010. 27(5): p. 56-65. [LA-UR-10-00667]
"Algorithms for optimal dyadic decision trees", Hush, D. and R. Porter, Machine Learning, 2010. 80(1): p. 85-107. [LA-UR-09-00704]
"Simulation framework for spatio-spectral anomalous change detection", Theiler, J.P., et al. in SPIE Defense, Security and Sensing. 2009. Orlando, FL.
"A framework for activity detection in wide-area motion imagery", Porter, R.B., C.E. Ruggiero, and J.D. Morrison. in SPIE Defense, Security and Sensing. 2009. Orlando, FL. [LA-UR-09-1629]
"Stack Filter Classifiers", Porter, R.B., D. Hush, and B.G. Zimmer. in International Symposium on Mathematical Morphology. 2009. Groningen, The Netherlands. [LA-UR-09-00530]
"A change detection approach to moving object detection in low frame-rate video", Porter, R.B., N.R. Harvey, and J.P. Theiler. in SPIE Defense Security and Sensing 2009. Orlando. [LA-UR-09-1796]
"Density-based similarity measures for content based search", Hush, D.R., R.B. Porter, and C.E. Ruggiero. in Asilomar Conference on Signals, Systems and Computers 2009. Pacific Grove, CA. [LA-UR-09-6762]
"A recurrent velocity filter for detecting large numbers of moving objects", Porter, R.B., et al. in SPIE Defense & Security Symposium. 2008. Orlando. [LA-UR-08-1029]
"Reliable computing with unreliable components: Using separable environments to stabilize long-term information storage", Nugent, M.A., R. Porter, and G.T. Kenyon, Physica D: Nonlinear Phenomena, 2008. 237(9): p. 1196-1206
"Improving multiple target tracking in structured environments using velocity priors", Loveland, R.C., E.J. Rosten, and R.B. Porter. in SPIE Defense and Security Symposium. 2008. Orlando. [LA-UR-08-916]
"Building robust appearance models using on-line feature selection. ", Porter, R.B., R. Loveland, and E.D. Rosten, in SPIE Defense and Security Symposium. 2007: Orlando. [LA-UR-07-0614]
"A reconfigurable computing framework for multi-scale cellular image processing", Porter, R., et al., Microprocess. Microsyst., 2007. 31(8): p. 546-563. [LA-UR-05-7448]
"Rotationally invariant sparse patch matching on GPU and FPGA", Baker, Z.K. and R.B. Porter. in IEEE Reconfigurable Architectures Workshop. 2007. MIAMI. [LA-UR-07-6858]
"A Run-Time Re-configurable Parametric Architecture for Local Neighborhood Image Processing", Porter, R.B., et al., in The Euromicro Conference on Digital System Design - DSD 2006. p. 107-115.
"A Programmable, Maximal Throughput Architecture for Neighborhood Image Processing", Porter, R., et al., in Proceedings of the 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines. 2006, IEEE Computer Society. p. 279-280.
"Image Processing Algorithms and Architectures for Reconfigurable Computers", Porter, R., in Reconfigurable Computing: Accelerating Computation with Field-Programmable Gate Arrays, Maya Gokhale and P. Graham, Editors. 2005, Springer. [LA-UR-01-1210]
"Spectral Morphology for Feature Extraction from Multi- and Hyper-Spectral Imagery", Harvey, N.R. and R.B. Porter, in SPIE Defense and Security Symposium, 2005. 2005: Orlando.
"A scalable learning system for video recognition", Porter, R.B., et al., in 2005 IEEE Aerospace Conference. 2004: Montana. [LA-UR-04-7701]
"Unsupervised adaptation to improve fault tolerance of neural network classifiers", Porter, R., A. Nugent, and G. Kenyon. in 2004 NAS/DOD Conference on Evolvable Hardware. 2004. Seatle. [LA-UR-04-1028]
"Weighted order statistic classifiers with large rank-order margin", Porter, R., et al. in 20TH International Conference on Machine Learning 2003. Washington. [LA-UR-03-0545]
"Optimizing Digital Hardware Perceptrons for Multi-Spectral Image Classification", Porter, R., et al., Journal of Mathematical Imaging and Vision, 2003. 19(2): p. 133-150. [LA-UR-03-0546]
"A multimodal approach to feature extraction for image and signal learning problems", Eads, D.R., et al. in SPIE 48TH Annual Meeting on Optimcal Science and Technology 2003. San Diego.
"Can pattern spectra be useful in hyper-spectral image analysis", Harvey, N.R., R.B. Porter, and A.C. Young. in IEEE-EURASIP Nonlinear Signal and Image Processing. 2001. Baltimore.
"ZEUS: Genetic Algorithms and Support Vector Machines for Time Series Classification", Eads, D.R., et al. in SPIE 47TH ANNUAL MEETING ; 200207 ; SEATTLE. 2001.
"Everything on the Chip: A Hardware-Based Self-Contained Spatially-Structured Genetic Algorithm for Signal Processing", Perkins, S., R.B. Porter, and N.R. Harvey, in Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware. 2000, Springer-Verlag. p. 165-174. [LA-UR-99-6843]
"An Applications Approach to Evolvable Hardware", Porter, R.B., K. Mc Cabe, and N. Bergmann. in NASA/DOD Workshop on Evolvable Hardware 1999. Pasadena.
