Faculty

Donald Geman

Professor

Research Interests

  • Image Analysis
  • Statistical Learning
  • Bioinformatics
Education
  • Ph.D. 1966, Northwestern University
  • B.A. 1965, University of Illinois
Research Areas
  • Computational Biology
  • Computer Vision
  • Computational Molecular Medicine
  • Statistical Learning
Awards
  • 2015:  Member
  • 2011:  Fellow - SIAM (Society for Industrial and Applied Mathematicians)
  • 1998:  Fellow - IMS (Institute of Mathematical Statistics)
Journal Articles
  • Blanchard, G., Geman, D.  Coarse-To-Fine Strategies for Pattern Recognition.
  • Ancona, A., Geman, D., Ikeda, N., Hennequin, P.  Comptes rendus... 21 Aout.-7 Sept., 1988, Saint-Flour.  Lecture notes in mathematics.
  • Yor, M., Younes, L., Amit, Y., Geman, D., Catoni, O.  D ETECTION HI ERARCHIQUE DE VISAGES PAR APPRENTISSAGE STATISTIQUE.
  • Ancona, A., Geman, D., Ikeda, N.  Ecole d’été de probabilités de Saint-Flour XVIII- 1988, Saint-Flour, 21 aout- 7 septembre 1988.  Lecture notes in mathematics.
  • cois Fleuret, F., Geman, D., Hall, C.  Fast Face Detection with Precise Pose Estimation.
  • Geman, D., Koloydenko, A.  Fort Collins, CO, June, 1999.(Published on Web)..
  • Fleuret, F., Geman, D.  Fort Collins, CO, June, 1999.(Published on Web)..
  • Geman, D.  INTERACTIVE SEARCH FOR IMAGE CATEGORIES BY MENTAL MATCHING.
  • Fan, X., Geman, D.  Learning Shape Hierarchies for Shape Detection.
  • Geman, D., Grimmett, G., Kelly, F., Papanicolaou, G., Pardoux, E.  Mathematical Economics and Finance and Applied Probability.
  • Pimentel, L., Mörters, P., Spohn, H., van Moerbeke, P., Takemura, A., Lifshits, M., van Zanten, H., Levin, D., Li, X., Li, D., others.  mathematics and statistics online.
  • Walks, C.  mathematics and statistics online.  Self.  86.  107.
  • Sánchez-Vega, F., Younes, L., Geman, D.  Predicting Gene Expression from TF Expression Reveals TF-TF Interactions in E. coli.
  • Rozovskii, B., Yor, M., Dawson, D., Geman, D., Grimmett, G., Karatzas, I., Kelly, F., Le Jan, Y., Papanicolaou, G.  Stochastic Mechanics Applications of.
  • Karatzas, I., Vor, M., Bremaud, P., Carlen, E., Fleming, W., Geman, D., Grimmett, G., Papanicolaou, G.  Stochastic Mechanics Applications of.
  • Afsari, B., Fertig, E., Geman, D., Marchionni, L.  switchBox: An R package for k-Top Scoring Pairs (kTSP) classifier development.
  • Gangaputra, S., Geman, D.  The Trace Model for Object Detection.
  • Geman, D., Ochs, M., Price, N., Tomasetti, C., Younes, L. (2014).  An argument for mechanism-based statistical inference in cancer.  Human genetics.  1–17.
  • Sfar, A., Boujemaa, N., Geman, D. (2014).  Confidence Sets for Fine-Grained Categorization and Plant Species Identification.  International Journal of Computer Vision.  1–21.
  • Afsari, B., Fertig, E., Younes, L., Geman, D., Marchionni, L. (2014).  Hardwiring mechanism into predicting cancer phenotypes by computational learning.  Cancer Research.  74(19 Supplement).  5342–5342.
  • Afsari, B., Geman, D., Fertig, E. (2014).  Learning Dysregulated Pathways in Cancers from Differential Variability Analysis.  Cancer informatics.  13(Suppl 5).  61.
  • Ma, S., Sung, J., Magis, A., Wang, Y., Geman, D., Price, N. (2014).  Measuring the Effect of Inter-Study Variability on Estimating Prediction Error.  PloS one.  9(10).  e110840.
  • Afsari, B., Neto, U., Geman, D. (2014).  Rank Discriminants for Predicting Phenotypes from RNA Expression.  arXiv preprint arXiv:1401.1490.
  • Afsari, B., Fertig, E., Geman, D., Marchionni, L. (2014).  switchBox: an R package for k–Top Scoring Pairs classifier development.  Bioinformatics.  btu622.
  • Geman, D., Ochs, M., Price, N., Tomasetti, C., Younes, E. (2014).  An argument for mechanism-based statistical inference in cancer..  Human genetics.
  • Marchionni, L., Afsari, B., Geman, D., Leek, J. (2013).  A simple and reproducible breast cancer prognostic test.  BMC genomics.  14(1).  336.
  • Sung, J., Kim, P., Ma, S., Funk, C., Magis, A., Wang, Y., Hood, L., Geman, D., Price, N. (2013).  Multi-study integration of brain cancer transcriptomes reveals organ-level molecular signatures.  PLoS computational biology.  9(7).  e1003148.
  • Simcha, D., Younes, L., Aryee, M., Geman, D. (2013).  Identification of direction in gene networks from expression and methylation..  BMC systems biology.  7.  118.
  • Sánchez-Vega, F., Younes, L., Geman, D. (2013).  Learning multivariate distributions by competitive assembly of marginals..  IEEE transactions on pattern analysis and machine intelligence.  35(2).  398-410.
  • Winslow, R., Trayanova, N., Geman, D., Miller, M. (2012).  Computational medicine: translating models to clinical care.  Science translational medicine.  4(158).  158rv11–158rv11.
  • Simcha, D., Price, N., Geman, D. (2012).  The limits of de novo DNA motif discovery.  PloS one.  7(11).  e47836.
  • Sánchez-Vega, F., Eisner, J., Younes, E., Geman, D. (2012).  Learning Multivariate Distributions by Competitive Assembly of Marginals.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  99.
  • Fleuret, F., Li, T., Dubout, C., Wampler, E., Yantis, S., Geman, D. (2011).  Comparing machines and humans on a visual categorization test.  Proceedings of the National Academy of Sciences.  108(43).  17621–17625.
  • Slama, P., Geman, D. (2011).  Identification of family-determining residues in PHD fingers.  Nucleic acids research.  39(5).  1666–1679.
  • Yörük, E., Ochs, M., Geman, D., Younes, L. (2011).  A comprehensive statistical model for cell signaling..  IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM.  8(3).  592-606.
  • Eddy, J., Hood, L., Price, N., Geman, D. (2010).  Identifying tightly regulated and variably expressed networks by Differential Rank Conservation (DIRAC).  PLoS computational biology.  6(5).  e1000792.
  • Eddy, J., Sung, J., Geman, D., Price, N. (2010).  Relative expression analysis for molecular cancer diagnosis and prognosis.  Technology in cancer research & treatment.  9(2).  149.
  • Geman, D. (2010).  STATISTICAL LEARNING IN COMPUTATIONAL BIOLOGY.  DESCRIPTIFS DES COURS DU M2 MVA MATH EMATIQUES VISION APPRENTISSAGE 2009-2010.
  • Leek, J., Scharpf, R., Bravo, H., Simcha, D., Langmead, B., Johnson, W., Geman, D., Baggerly, K., Irizarry, R. (2010).  Tackling the widespread and critical impact of batch effects in high-throughput data.  Nature Reviews Genetics.  11(10).  733–739.
  • Ferecatu, M., Geman, D. (2009).  A statistical framework for image category search from a mental picture.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  31(6).  1087–1101.
  • Lin, X., Afsari, B., Marchionni, L., Cope, L., Parmigiani, G., Naiman, D., Geman, D. (2009).  Address: 1Department of Applied Mathematics and Statistics, The Johns Hopkins University, Baltimore, Maryland, USA, 2Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, Maryland, USA, 3Department of Oncology, The Johns Hopkins Kimmel Cancer Center, Baltimore, Maryland, USA, 4Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA and 5Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland, USA.  BMC Bioinformatics.  10.  256.
  • Lin, X., Afsari, B., Marchionni, L., Cope, L., Parmigiani, G., Naiman, D., Geman, D. (2009).  The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations.  BMC bioinformatics.  10(1).  256.
  • Edelman, L., Toia, G., Geman, D., Zhang, W., Price, N. (2009).  Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases.  BMC genomics.  10(1).  583.
  • Geman, Marin Ferecatu—Donald., Ferecatu, M., others. (2008).  A Statistical Framework for Image Category Search from a Mental Picture.
  • Xu, L., Tan, A., Winslow, R., Geman, D. (2008).  Merging microarray data from separate breast cancer studies provides a robust prognostic test.  Bmc Bioinformatics.  9(1).  125.
  • Eddy, J., Geman, D., Price, N. (2008).  Pathway Expression Rank Analysis (p-XRAY): A Novel Tool for Gene Set Expression Analysis.  The 2008 Annual Meeting.
  • Wang, J., Geman, D., Luo, J., Gray, R. (2008).  Real-world image annotation and retrieval: an introduction to the special section.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  30(11).  1873–1876.
  • Geman, Marin Ferecatu—Donald. (2008).  Semantic Image Category Search from a Mental Picture.
  • Wang, J., Geman, D., Luo, J., Gray, R. (2008).  SPECIAL SECTION ON REAL-WORLD IMAGE ANNOTATION AND RETRIEVAL-Real-World Image Annotation and Retrieval: An Introduction to the Special Section.  IEEE Transactions on Pattern Analysis and Machine Intelligence.  30(11).  1873.
  • Fleuret, F., Geman, D. (2008).  Stationary features and cat detection.  Journal of Machine Learning Research.  9(2549-2578).  16.
  • Anderson, T., Tchernyshyov, I., Diez, R., Cole, R., Geman, D., Dang, C., Winslow, R. (2007).  Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data..  Proteomics.  7(8).  1197–1207.
  • Xu, L., Geman, D., Winslow, R. (2007).  Large-scale integration of cancer microarray data identifies a robust common cancer signature.  BMC bioinformatics.  8(1).  275.
  • Sahbi, H., Geman, D. (2006).  A hierarchy of support vector machines for pattern detection.  The Journal of Machine Learning Research.  7.  2087–2123.
  • Blanchard, G., Geman, D. (2005).  EPrint Removed.  Annals of Statistics.  33(3).  1155–1202.
  • Blanchard, G., Geman, D. (2005).  Hierarchical testing designs for pattern recognition.  Annals of Statistics.  1155–1202.
  • Koloydenko, A., Geman, D. (2005).  Ordinal coding of image microstructure.  Eurandom.
  • Xu, L., Tan, A., Naiman, D., Geman, D., Winslow, R. (2005).  Robust prostate cancer marker genes emerge from direct integration of inter-study microarray data.  Bioinformatics.  21(20).  3905–3911.
  • Tan, A., Naiman, D., Xu, L., Winslow, R., Geman, D. (2005).  Simple decision rules for classifying human cancers from gene expression profiles.  Bioinformatics.  21(20).  3896–3904.
  • Geman, D., Koloydenko, A. (2005).  Spatial Adaptation in Coding Microstructure of Natural Images..
  • Amit, Y., Geman, D., Fan, X. (2004).  A coarse-to-fine strategy for multiclass shape detection.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  26(12).  1606–1621.
  • Geman, D., d’Avignon, C., Naiman, D., Winslow, R. (2004).  Classifying gene expression profiles from pairwise mRNA comparisons.  Statistical applications in genetics and molecular biology.  3(1).
  • Geman, D., d’Avignon, C., Naiman, D., Winslow, R., Zeboulon, A. (2004).  Gene expression comparisons for class prediction in cancer studies.  Proceedings 36’th Symposium on the Interface: Computing Science and Statistics.
  • Geman, D. (2004).  Study around path classification in a ternary tree.
  • Geman, D. (2003).  Mathematical Sciences 550: 437 Information, Statistics and Perception.
  • d’Avignon, C., Geman, D. (2003).  Tree-structured neural decoding.  The Journal of Machine Learning Research.  4.  743–754.
  • Fleuret, F., Geman, D. (2001).  Coarse-to-fine face detection.  International Journal of computer vision.  41(1-2).  85–107.
  • Geman, D., Jedynak, B. (2001).  Model-based classification trees.  IEEE Transactions on Information Theory.  47(3).  1075–1082.
  • Geman, D., Moquet, R. (2000).  A stochastic feedback model for image retrieval.  Proc. RFIA.  3.  173–180.
  • cois Fleuret, F., Geman, D. (2000).  Coarse-to-Fine Face Detection.  Citeseer.
  • Geman, D., Moquet, R. (2000).  Q & a models for interactive search.  Preprint, December.
  • Amit, Y., Geman, D. (1999).  A computational model for visual selection.  Neural computation.  11(7).  1691–1715.
  • cois Fleuret, F., Geman, D. (1999).  Coarse-to-Fine Visual Selection.  Citeseer.
  • Fleuret, F., Geman, D. (1999).  Coarse-to-fine visual selection.  Citeseer.
  • cois Fleuret, F., Geman, D. (1999).  Graded Learning for Object Detection.  Citeseer.
  • Fleuret, F., Geman, D. (1999).  Graded learning for object detection.  Proc. IEEE Workshop Statistical and Computational Theories of Vision.  544–549.
  • Geman, D., Koloydenko, A. (1999).  Invariant statistics and coding of natural microimages.  IEEE Workshop on Statistical and Computational Theories of Vision.
  • Geman, D. (1999).  Statistical Learning and Coarse-to-fine Object Detection.  COMPUTING SCIENCE AND STATISTICS.  60–60.
  • Amit, Y., Geman, D. (1998).  Discussion: Arcing Classifiers.  Annals of Statistics.  833–837.
  • Geman, D., Amit, Y., Wilder, K. (1997).  Joint induction of shape features and tree classifiers.  Citeseer.
  • Amit, Y., Geman, D., Wilder, K. (1997).  Joint induction of shape features and tree classifiers.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  19(11).  1300–1305.
  • Amit, Y., Geman, D. (1997).  Shape quantization and recognition with randomized trees.  Neural computation.  9(7).  1545–1588.
  • Geman, D., Jedynak, B. (1996).  An active testing model for tracking roads in satellite images.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  18(1).  1–14.
  • Geman, D. (1996).  Wiley & Sons, 1989. 1181 C. Goad,” Special purpose automatic programming for three-dimensional model-based vision,” Proc. ARPA Image Understand-ing Workshop, pp. 94-104, 1983. 1191 C. Graffigne and I. Herlin,” Mod6lisation de reseaux pour.  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE.  18(1).
  • Geman, D., Yang, C. (1995).  Nonlinear image recovery with half-quadratic regularization.  Image Processing, IEEE Transactions on.  4(7).  932–946.
  • Clifford, P., JENNISON, C., WAKEFIELD, J., PHILLIPS, D., FRIGESSI, A., GRAY, A., LAWSON, A., FORSTER, J., RAMGOPAL, P., ARSLAN, O., others. (1993).  DISCUSSION ON THE MEETING ON THE GIBBS SAMPLER AND OTHER MARKOV CHAIN-MONTE CARLO METHODS.  J ROY STAT SOC B MET.  55(1).  53–102.
  • Geman, D., Jedynak, B., others. (1993).  Shape recognition and twenty questions.
  • Geman, S., Geman, D. (1993).  Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images*.  Journal of Applied Statistics.  20(5-6).  25–62.
  • Geman, S., McClure, D., Geman, D. (1992).  A nonlinear filter for film restoration and other problems in image processing.  CVGIP: Graphical models and image processing.  54(4).  281–289.
  • Geman, D., Reynolds, G. (1992).  Constrained restoration and the recovery of discontinuities.  IEEE Transactions on pattern analysis and machine intelligence.  14(3).  367–383.
  • GEMAN, S., Geman, D. (1992).  Reprinted with permission from IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. PAMI-6 (6), pp. 721-741 (November 1984). 1984 IEEE..  Selected papers on digital image restoration.  47.  263.
  • Geman, D., Gidas, B. (1991).  Image analysis and computer vision.  Spatial statistics and digital image analysis.  9–36.
  • Geman, D., Geman, S., Graffigne, C., Dong, P. (1990).  Boundary detection by constrained optimization.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  12(7).  609–628.
  • Geman, D., Grenander, U., Piccioni, M., Presutti, E. (1990).  Fees and registration.  Signal Processing.  20.  189–191.
  • Geman, D., Branch, B. (1988).  The Valuation of Stochastic Cash Flows.  Quarterly Journal of Business and Economics.  148–178.
  • Geman, D. (1987).  Stochastic model for boundary detection.  Image and Vision Computing.  5(2).  61–65.
  • Geman, D. (1985).  Bayesian image analysis by adaptive annealing.  IEEE Transactions on Geoscience and Remote Sensing.  1.  269–276.
  • Geman, D., Horowitz, J., Rosen, J. (1984).  A local time analysis of intersections of Brownian paths in the plane.  The Annals of Probability.  86–107.
  • Derin, H., Elliott, H., Cristi, R., Geman, D. (1984).  Bayes smoothing algorithms for segmentation of binary images modeled by Markov random fields.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  (6).  707–720.
  • Geman, S., Geman, D. (1984).  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images.  Pattern Analysis and Machine Intelligence, IEEE Transactions on.  (6).  721–741.
  • Geman, D., Horowitz, J., Rosen, J., Karatzas, I., Stout, Q., Warren, B., Mason, D., Yamato, H. (1982).  THE ANNALS.  The Annals of Statistics.  10(2).
  • Geman, D., Horowitz, J. (1981).  Smooth perturbations of a function with a smooth local time.  Transactions of the American Mathematical Society.  267(2).  517–530.
  • Geman, D. (1980).  Confluent Brownian Motions.  Advances in Applied Probability.  306–306.
  • Geman, D., Horowitz, J. (1980).  Occupation densities.  The Annals of Probability.  1–67.
  • Geman, D., HOROWITZ, J. (1980).  SPECIAL INVITED PAPER.  The Annals of Probability.  8(1).  1–67.
  • Densities, O., Geman, D., Horowitz, J., Philipp, W., Ghoussoub, N., Steele, J., Metivier, M., Pellaumail, J., Diaconis, P., Freedman, D., others. (1980).  Special Invited Paper.
  • Geman, D. (1979).  Dispersion points for linear sets and approximate moduli for some stochastic processes.  Transactions of the American Mathematical Society.  253.  257–272.
  • Geman, D., Zinn, J. (1978).  On the increments of multidimensional random fields.  The Annals of Probability.  151–158.
  • Cuzick, J., Hosoya, Y., Portnoy, S., Steele, J., Shields, P., Neuhoff, D., Davisson, L., Ledrappier, F., Geman, D., Zinn, J. (1978).  VOLUME 6 February 1978 No..  THE ANNALS OF PROBABILITY.  6(1).
  • Geman, D. (1977).  On the approximate local growth of multidimensional random fields.  Probability Theory and Related Fields.  38(3).  237–251.
  • Geman, D. (1976).  A note on the continuity of local times.  Proceedings of the American Mathematical Society.  321–326.
  • Geman, D., Horowitz, J. (1976).  Local times for real and random functions.  Duke Mathematical Journal.  43(4).  809–828.
  • Geman, D., Horowitz, J. (1976).  Occupation-times for functions with countable level sets and the regeneration of stationary processes.  Probability Theory and Related Fields.  35(3).  189–211.
  • Geman, D., Horowitz, J., Zinn, J. (1976).  Recurrence of stationary sequences.  The Annals of Probability.  372–381.
  • Mitt-vl, Y., Ylvisaker, D., Geman, D., Horowitz, J., Zinn, J., Gianini, J., Samuels, S., Tomkins, I., Hwang, J. (1976).  THE ANNALS.  The Annals of Probability.  4(3).
  • Geman, D., Horowitz, J. (1975).  Polar sets and Palm measures in the theory of flows.  Transactions of the American Mathematical Society.  208.  141–159.
  • Geman, D., Horowitz, J. (1975).  RANDOM SHIFTS WHICH PRESERVE MEASURE1.  AMERICAN MATHEMATICAL SOCIETY.  49(1).
  • Geman, D., Horowitz, J. (1974).  Local times and supermartingales.  Probability Theory and Related Fields.  29(4).  273–293.
  • Geman, D., Horowitz, J. (1974).  Transformations of flows by discrete random measures.  INDIANA UNIVERSITY MATHEMATICS JOURNAL.  24(4).  291–306.
  • Geman, D. (1973).  A note on the distribution of hitting times.  The Annals of Probability.  1(5).  854–856.
  • Klass, M., Lloyd, S., Mallows, C., Blackwell, D., Freedman, D., Logan, B., Mallows, C., Rice, S., Shepp, L., Chow, Y., others. (1973).  An Official Journal of the Institute of Mathematical Statistics..
  • Geman, D., Horowitz, J. (1973).  Occupation times for smooth stationary processes.  The Annals of Probability.  1(1).  131–137.
  • Geman, D., Horowitz, J. (1973).  Remarks on Palm measures.  Annales de l’institut Henri Poincaré (B) Probabilités et Statistiques.  9(3).  215–232.
  • Geman, D., Horowitz, J. (1973).  Remarks on Palm measures.  Annales de l’institut Henri Poincaré (B) Probabilités et Statistiques.  9(3).  215–232.
  • Burkholder, D. (1973).  The 1971 Wald Memorial Lectures,".  Annals of Probability.  1.  19–42.
  • Kesten, H., Taylor, H., Rosen, B., Fraser, D., van Eeden, C., McCabe, G., Gupta, S., Panchapakesan, S., Johnson, R., Mehrotra, K., others. (1972).  Miscellaneous front pages, Ann. Math. Statist., Volume 43, Number 3 (1972).
  • Geman, D. (1972).  On the variance of the number of zeros of a stationary Gaussian process.  The Annals of Mathematical Statistics.  977–982.
  • Johnson, R., Mehrotra, K., Koul, H., Staddte, Jr, R., Fraser, D., Fishburn, P., Johns, Jr, M., Van Ryzin, J., Martin, R., Schwartz, S., others. (1972).  THE ANNALS.
Books
  • Ancona, A., Geman, D., Ikeda, N. (1991).  École d’été de probabilités de Saint-Flour XVIII-1988.  Springer.  18.
  • Ancona, A., Geman, D., Ikeda, N., Hennequin, P. L. (1990).  Probabilites.  Springer-Verlag.
  • Geman, D., Geman, S. A. (1987).  Relaxation and annealing with constraints.  Center for Intelligent Control Systems.
Book Chapters
  • Gangaputra, S., Geman, D. (2006).  The trace model for object detection and tracking.  Toward Category-Level Object Recognition.  Springer.  401–420.
  • Fang, Y., Geman, D. (2005).  Experiments in mental face retrieval.  Audio-and Video-Based Biometric Person Authentication.  Springer.  637–646.
  • Geman, D. (2003).  Coarse-to-fine classification and scene labeling.  Nonlinear Estimation and Classification.  Springer New York.  31–48.
  • Amit, Y., Geman, D., Jedynak, B. (1998).  Efficient focusing and face detection.  Face Recognition.  Springer Berlin Heidelberg.  157–173.
  • Jung, F., Jedynak, B., Geman, D. (1997).  Recognizing buildings in aerial images.  Automatic Extraction of Man-Made Objects from Aerial and Space Images (II).  Birkhäuser Basel.  173–182.
  • Kepner, J., Horowitz, J., Geman, D. (1994).  Computation of IRAS Fluxes via a Priori Astrometry.  Infrared Astronomy with Arrays.  Springer.  179–180.
  • Geman, D. (1990).  Random fields and inverse problems in imaging.  École d’Été de Probabilités de Saint-Flour XVIII-1988.  Springer Berlin Heidelberg.  113–193.
  • Geman, D., Geman, S., Graffigne, C. (1987).  Locating texture and object boundaries.  Pattern Recognition Theory and Applications.  Springer.  165–177.
  • Geman, D., Geman, S. (1986).  Bayesian image analysis.  Disordered Systems and Biological Organization.  Springer.  301–319.
Other Publications
  • Price, N. D., Hood, L., Sung, J., Geman, D. (2015).  DETECTION OF BRAIN CANCER TYPES.
  • Manbeck, K., Geman, D., Geman, S., others. (2007).  Automated color control in film-to-digital transfer.  Google Patents.
  • Manbeck, K., Cassidy, J., Geman, S., Geman, D., McClure, D., others. (2006).  High resolution color conforming.  Google Patents.
  • Manbeck, K., Geman, D., Geman, S., Orton, M. N., others. (2006).  Automated color control in film-to-digital transfer.  Google Patents.
  • Yang, C., Manbeck, K., Geman, S., Geman, D., others. (2006).  Format conversion.  Google Patents.
  • Amit, Y., Geman, D., Fan, X. (2003).  Computational strategies for model-based scene interpretation.  Technical report, The Johns Hopkins University, 2003. http://www. cis. jhu. edu/ xdfan/strategies. pdf.
  • Manbeck, K., Yang, C., Geman, D., Geman, S. (2003).  Video field labeling.  Google Patents.
  • Manbeck, K., Yang, C., Geman, D., Geman, S. (2003).  Cadence editing.  Google Patents.
  • Geman, D., Geman, S., Manbeck, K. (2002).  Automated color control in film-to-digital transfer.
  • Cassidy, J., Geman, D., Geman, S., Manbeck, K., McClure, D. (2002).  High resolution color conforming.
  • Krempp, S., Geman, D., Amit, Y. (2002).  Sequential learning of reusable parts for object detection.  Technical report, CS Johns Hopkins.
  • MANBECK, K., CASSIDY, J., GEMAN, S., Geman, D., MCCLURE, D. (2002).  HIGH RESOLUTION IMAGE COLOR CORRECTION METHOD AND SYSTEM.
  • Manbeck, K., Yang, C., Geman, D., Geman, S. (2002).  SYSTEM AND METHOD FOR IDENTIFYING INCONSISTENCIES IN DUPLICATE DIGITAL VIDEOS.
  • Geman, D., Geman, S., Manbeck, K., Yang, C. (2001).  Format conversion.
  • YANG, C., MANBECK, K., GEMAN, S., Geman, D. (2001).  FORMAT CONVERSION.
  • MANBECK, K., YANG, C., Geman, D., GEMAN, S. (2001).  SYSTEM AND METHOD FOR IDENTIFYING INCONSISTENCIES IN DUPLICATE DIGITAL VIDEOS.
  • MANBECK, K., YANG, C., Geman, D., GEMAN, S. (2001).  METHOD AND APPARATUS FOR CADENCE EDITING OF DIGITAL VIDEO FIELD SEQUENCES.
  • MANBECK, K., YANG, C., Geman, D., GEMAN, S. (2001).  VIDEO FIELD LABELING.
  • Amit, Y., Geman, D. (1998).  Arcing classifiers-Discussion.  INST MATHEMATICAL STATISTICS IMS BUSINESS OFFICE-SUITE 7, 3401 INVESTMENT BLVD, HAYWARD, CA 94545 USA.
  • Amit, Y., Geman, D. (1994).  Randomized Inquiries About Shape: An Application to Handwritten Digit Recognition..  DTIC Document.
  • Geman, D., Geman, S., Gidas, B., Grenander, U., McClure, D. E. (1991).  A Mathematical Framework for Image Analysis.  DTIC Document.
  • Geman, D., Geman, S. (1991).  BAYESIAN IMAGE-RESTORATION, WITH 2 APPLICATIONS IN SPATIAL STATISTICS-DISCUSSION.  Annals of the Institute of Statistical Mathematics.  43(1).  21–22.
  • Bienenstock, E., Geman, D., Geman, S., McClure, D. E. (1990).  Development of Laser Radar ATR Algorithms: Phase 2. Military Objects.  DTIC Document.
  • Geman, S., Geman, D., McClure, D. E., Grenander, U. (1987).  A Unified Mathematical Approach to Image Analysis..  DTIC Document.
  • McClure, D. E., Geman, S., Geman, D., Grenander, U. (1987).  Image Modeling: A Mathematical Framework for Segmentation and Object Detection..  DTIC Document.
  • Elliott, H., Derin, H., Cristi, R., Geman, D. (1983).  Application of the Gibbs Distribution to Image Segmentation..  MASSACHUSETTS UNIV AMHERST DEPT OF ELECTRICAL AND COMPUTER ENGINEERING.
  • Derin, H., Elliott, H., Cristi, R., Geman, D. (1983).  Bayes Smoothing Algorithms for Segmentation of Images Modelled by Markov Random Fields..  DTIC Document.
  • Geman, D. (1977).  Singularities in the Distribution of the Increments of a Smooth Function..  DTIC Document.
  • Geman, D. (1970).  Horizontal-window Conditioning and the Zeros of Stationary Processes.  Northwestern University.
Conference Proceedings
  • Rejeb Sfar, A., Boujemaa, N., Geman, D. (2013).  Identification of plants from multiple images and botanical idkeys.  Proceedings of the 3rd ACM conference on International conference on multimedia retrieval.  191–198.
  • Sfar, A. R., Boujemaa, N., Geman, D. (2013).  Vantage Feature Frames For Fine-Grained Categorization.  Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on.  835–842.
  • Eddy, J. A., Geman, D., Price, N. D. (2009).  Relative expression analysis for identifying perturbed pathways.  Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE.  5456–5459.
  • Ferecatu, M., Geman, D. (2007).  Interactive search for image categories by mental matching.  Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on.  1–8.
  • Gangaputra, S., Geman, D. (2006).  A design principle for coarse-to-fine classification.  Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on.  2.  1877–1884.
  • Wang, J. Z., Boujemaa, N., Del Bimbo, A., Geman, D., Hauptmann, A. G., Tesic, J. (2006).  Diversity in multimedia information retrieval research.  Proceedings of the 8th ACM international workshop on Multimedia information retrieval.  5–12.
  • Geman, D. (2006).  In Search of a Unifying Theory for Image Interpretation.  Information Theory, 2006 IEEE International Symposium on.  xliv–xliv.
  • Geman, D. (2006).  Interactive image retrieval by mental matching.  Proceedings of the 8th ACM international workshop on Multimedia information retrieval.  1–2.
  • Gangaputra, S., Geman, D. (2005).  A unified stochastic model for detecting and tracking faces.  Computer and Robot Vision, 2005. Proceedings. The 2nd Canadian Conference on.  306–313.
  • Fang, Y., Geman, D., Boujemaa, N. (2005).  An interactive system for mental face retrieval.  Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval.  193–200.
  • Fan, X., Geman, D. (2004).  Hierarchical object indexing and sequential learning.  Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on.  3.  65–68.
  • Gangputra, S., Geman, D. (2004).  Self-normalized linear tests.  Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on.  2.  II–616.
  • Sahbi, H., Geman, D., Boujemaa, N. (2002).  Face detection using coarse-to-fine support vector classifiers.  Image Processing. 2002. Proceedings. 2002 International Conference on.  3.  925–928.
  • Fleuret, F., Geman, D. (2002).  Fast face detection with precise pose estimation.  Pattern Recognition, 2002. Proceedings. 16th International Conference on.  1.  235–238.
  • Geman, D. (1994).  The entropy strategy for shape recognition.  Information Theory and Statistics, 1994. Proceedings., 1994 IEEE-IMS Workshop on.  8.
  • Geman, D., Horowitz, J. (1993).  Searching for Circumstellar Disks with Space Telescope Observations.  Information Theory, 1993. Proceedings. 1993 IEEE International Symposium on.  133–133.
  • Geman, D., Jedynak, B. (1991).  Detection of roads in satellite images.  Geoscience and Remote Sensing Symposium, 1991. IGARSS’91. Remote Sensing: Global Monitoring for Earth Management., International.  4.  2473–2477.
  • Geman, D. (1991).  Remarks on Hard Modeling vs. Image Processing, Circumstellar Disks and Model Validation.  The Restoration of HST Images and Spectra.  1.  74.
  • Geman, D., GEMAN, S., GRENANDER, U., MCCLURE, D. (1984).  THE PARALLEL REALIZATION OF MARKOV RANDOM-FIELDS WITH APPLICATIONS TO PROBLEMS IN INFERENCE AND OPTIMIZATION.  STOCHASTIC PROCESSES AND THEIR APPLICATIONS.  17(1).  34–35.
  • HOROWITZ, J., Geman, D. (1971).  PALM PROBABILITIES AND ADDITIVE FUNCTIONALS. 1. PRELIMINARY REPORT.  NOTICES OF THE AMERICAN MATHEMATICAL SOCIETY.  18(6).  972.
  • Geman, D. (1971).  VARIANCE OF NUMBER OF ZEROS OF A STATIONARY GAUSSIAN PROCESS.  ANNALS OF MATHEMATICAL STATISTICS.  42(5).  1794.
  • "A visual Turing test for computer vision systems", ONR Workshop.  Durham, North Carolina.  October 25, 2015
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