Donald Genam, Professor of Mathematics Illustration of profile with glowing brain and sight lines
  Johns Hopkins University
 

SOME PUBLICATIONS

  • X. Lin, B. Afsari, L. Marchionni, L. Cope, G. Parmigiani, D. Naiman and D. Geman, "The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations," BMC Bioinformatics 10:256, 2009. (pdf)
  • M. Ferecatu and D. Geman, "A statistical framework for image category search from a mental picture," IEEE Trans. PAMI, 31, 1087-1101, 2009. (pdf)
  • D. Geman, B. Afsari, A.C. Tan and D. Naiman "Microarray classification from several two-gene experssion comparisons," Proceedings ICMLA, 2008 (Winner, ICMLA Microarray Classification Algorithm Competition). (pdf)
  • F. Fleuret and D. Geman, "Stationary features and cat detection," Journal of Machine Learning Research, 9:2549-2578, 2008. (pdf)
  • L. Xu, A.C. Tan, R. L. Winslow and D. Geman, "Merging microarray data from separate breast cancer studies provides a robust prognostic signature," BMC Bioinformatics 9:125, 2008. (pdf)
  • M. Ferecatu and D. Geman, "Interactive search for image categories by mental matching," Proceedings Inter. Conf. on Computer Vision (ICCV '07) , Rio de Janeiro, October 14-20, 2007. (pdf)
  • T.J. Anderson, I. Tchernyshyov, R. Diez, R.N. Cole, D. Geman, C.V. Dang and R. Winslow, "Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data," Proteomics 7: 1197-1207, 2007. (pdf)
  • L. Xu, D. Geman and R. Winslow, "Large-scale integration of cancer microarray data identifies a robust common cancer signature," BMC Bioinformatics 8:275, 2007. (pdf)
  • S. Gangaputra and D. Geman, "A design principle for coarse-to-fine classification," Proceedings CVPR 2006, 2, 1877-1884, 2006. (pdf)
  • A. Koloydenko and D. Geman, "Ordinal coding of image microstructure," Proceedings Inter. Conf. Image Processing, Computer Vision and Pattern Recognition (IPCV'06), Las Vegas, NV, June, 2006. (pdf)
  • S. Gangaputra and D. Geman, "The trace model for object detection and tracking," Toward Category-Level Object Recognition (eds. J. Ponce et al), Lecture Notes in Computer Science, 4170, 401-420, 2006. (pdf)
  • H. Sahbi and D. Geman, "A hierarchy of support vector machines for pattern detection," Journal of Machine Learning Research, 7, 2087-2123, 2006. (pdf)
  • L. Xu, A-C Tan, D. Naiman, D. Geman and R. Winslow, "Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data," Bioinformatics , 21, 3905-3911, 2005. (pdf)
  • A-C Tan, D. Naiman, L. Xu, R. Winslow and D. Geman, "Simple decision rules for classifying human cancers from gene expression profiles," Bioinformatics , 21, 3896-3904, 2005. (pdf)
  • Y. Fang and D. Geman, "Experiments in mental face retrieval," Proceedings AVBPA 2005, Lecture Notes in Computer Science, 637-646, July 2005. (Best Student Paper Award) (pdf)
  • S. Gangaputra and D. Geman, "A unified stochastic model for detecting and tracking faces," Proceedings Second Canadian Conf. on Computer and Robot Vision (CRV'05), 306-313, 2005. (pdf)
  • G. Blanchard and D. Geman, "Sequential testing designs for pattern recognition," Annals of Statistics, 33, 1155-1202, June, 2005. (pdf)
  • D. Geman, C. d'Avignon, D. Naiman, R. Winslow and A. Zeboulon, "Gene expression comparisons for class prediction in cancer studies," Proceedings 36'th Symposium on the Interface: Computing Science and Statistics, 2004. (pdf)
  • Y. Amit, D. Geman and X. Fan, "A coarse-to-fine strategy for multi-class shape detection,"  IEEE Trans. PAMI, 28, 1606-1621,  2004. (pdf)
  • D. Geman, C. d'Avignon, D. Naiman and R. Winslow, "Classifying gene expression profiles from pairwise mRNA comparisons," Statist. Appl. in Genetics and Molecular Biology, 3, 2004. (pdf)
  • S. Gangaputra and D. Geman, "Self-normalized linear tests," Proceedings CVPR 2004, 2, 616-622, 2004 (pdf)
  • X. Fan and D. Geman, "Hierarchical object indexing and sequential learning," Proceedings ICPR 2004, 3, 65-68, 2004. (pdf)
  • D. Geman, "Coarse-to-fine classification and scene labeling," Nonlinear Estimation and Classification (eds. D. D. Denison et al.), Lecture Notes in Statistics. New York: Springer-Verlag, 31-48, 2003. (pdf)
  • C. d'Avignon and D. Geman, "Tree-structured neural decoding ," Journal of Machine Learning Research, 4, 743-754, 2003. (pdf)
  • H. Sahbi, D. Geman and N. Boujemaa, "Face detection using coarse-to-fine support vector classifiers," Proceedings ICIP-02, 3, 925-928, 2002. (pdf)
  • F. Fleuret and D. Geman, "Fast face detection with precise pose estimation," Proceedings ICPR2002, 1, 235-238, 2002. (pdf)
  • S. Krempp, D. Geman and Y. Amit, "Sequential learning with reusable parts for object detection," Technical Report, 2002. (pdf)
  • F. Fleuret and D. Geman, "Coarse-to-fine face detection," Inter. Journal of Computer Vision, 41, 85-107, 2001. (pdf)
  • D. Geman and B. Jedynak, "Model-based classification trees," IEEE Trans. Info. Theory, 47, 1075-1082, 2001. (pdf)
  • D. Geman and R. Moquet, "Q & A models for interactive search," Technical Report, 2001. (pdf)
  • D. Geman, "Interrogation Bayesienne d'une base de donnees," Proceedings 33rd Journees de Statistique, Nantes, 15-20, 2001.
  • D. Geman and R. Moquet, "A stochastic model for image retrieval," Proc. RFIA 200, Paris, February, 2000. (pdf)
  • F. Fleuret and D. Geman, "Graded learning for object detection," Proceedings IEEE Workshop on Statistical and Computational Theories of Vision, Fort Collins, CO, June, 1999.
  • D. Geman and A. Koloydenko, "Invariant statistics and coding of natural microimages," Proceedings, IEEE Workshop on Statistical and Computational Theories of Vision, Fort Collins, CO, June, 1999. (pdf)
  • Y. Amit and D. Geman, "A computational model for visual selection," Neural Computation, 11, 1691-1715, 1999. (pdf)
  • C. Li and D. Geman, "Active testing at multiple resolutions," Proceedings ASA Conference, Baltimore, 1999.
  • Y. Amit, D. Geman and B. Jedynak, " Efficient focusing and face detection," Face Recognition: From Theory to Applications, eds. H. Wechsler et al, NATO ASI Series F, Springer-Verlag, Berlin, 157-173, 1998. (pdf)
  • F. Jung, B. Jednyak and D. Geman, "Recognizing buildings in aerial images," Automatic Extraction of Man-Made Objects from Aerial and Space Images, II, Birkhauseer (Basel), Ascona, 173-182, May, 1997.
  • Y. Amit, D. Geman and K. Wilder, " Joint induction of shape features and tree classifiers," IEEE Trans. Pattern Anal. Mach. Intell., 19, 1300-1305, 1997. (pdf)
  • Y. Amit and D. Geman, "Shape quantization and recognition with randomized trees," Neural Computation., 9, 1545-1588, 1997. (pdf)
  • D. Geman and B. Jedynak, "An active testing model for tracking roads from satellite images," IEEE Trans. Pattern Anal. Mach. Intell, 18, 1-14, 1996. (pdf)
  • D. Geman and C. Yang, "Nonlinear image recovery with half-quadratic regularization," IEEE Trans. Image Processing, 4, 932-946, 1995. (pdf)
  • S. Geman and D. Geman, "Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Mach. Intell, 6, 721-741, 1984. (pdf)