Veröffentlichungen und Vorträge

Dissertation

[1] H. Schramm, "Modeling spontaneous speech variability for large vocabulary continuous speech recognition", RWTH Aachen, Computer Science Department, April 2006.

Buchbeiträge

[2] C.Meyer, H. Schramm, "Machine Learning in Automatic Speech Recognition: Boosting and Discriminative Training of the Acoustic Model", in Machine Learning Research Progress, Editors: H. Peters, M. Vogel, ISBN: 978-1-60456-646-8, 2008.

Journalbeiträge

[3] B. Souvignier, A. Kellner, B. Rueber, H. Schramm, F. Seide. "The thoughtful elephant: Strategies for spoken dialog systems", IEEE Transactions on Speech and Audio Processing, 8(1):51 -- 62, January 2000.

[4] H. Schramm, B. Rueber, and A. Kellner, "Strategies for name recognition in automatic directory assistance systems", Invited Paper, Speech Communication Journal, pp. 329 -- 338, Volume 31, Issue 4, August 2000.

[5] H. Schramm, X. Aubert, B. Bakker, C. Meyer, H. Ney, "Modeling spontaneous speech variability in professional dictations", Speech Communication Journal, Vol. 48, Issue 5, pp. 493-515, May 2006.

[6] C. Meyer, H. Schramm, "Boosting acoustic models for large vocabulary continuous speech recognition", Speech Communication Journal, Vol. 48, Issue 5, pp. 532-548, May 2006.

[7] O. Ecabert, J. Peters, H. Schramm, C. Lorenz, J. v. Berg, M. J. Walker, M. Vembar, M. E. Olszewski, K. Subramanyan, G. Lavi, and J. Weese. "Automatic Model-based Segmentation of the Heart in CT Images", IEEE Transactions on Medical Imaging, Volume 27, Issue 9, Sept. 2008 Page(s):1189 - 1201.

[8] H. Ruppertshofen, C. Lorenz, P. Beyerlein, Z. Salah, G. Rose, H. Schramm, “Discriminative Generalized Hough Transform for Localization of Joints in Lower Limbs”, Computer Science – Research and Development Journal, 2010.

[9] M. Harmsen, B. Fischer, H. Schramm, T. Seidel, T. Deserno, “Support Vector Machine Classification based on Correlation Prototypes applied to Bone Age Assessment”, IEEE Transactions on Information Technology in BioMedicine.

[10] H. Ruppertshofen, C. Lorenz, G. Rose, H. Schramm, „Discriminative Generalized Hough Transform for Object Localization in Medical Images”, International Journal of Computer Assisted Radiology and Surgery, accepted for publication, Jan. 2013.

[11] E. Gabriel, M. Schleiss, H. Schramm, C. Meyer, "Analysis of the Discriminative Generalized Hough Transform as a Proposal Generator for a Deep Network in Automatic Pedestrian and Car Detection," Journal of Electronic Imaging 27(5), 051228, 2018.

[12] A. O. Mader, C. Lorenz, M. Bergtholdt, J. von Berg, H. Schramm, J. Modersitzky, C. Meyer, "Detection and localization of spatially correlated point landmarks in medical images using an automatically learned conditional random field", Journal Computer Vision and Image Understanding, Volumes 176–177, Pages 45-53, November–December 2018.

[13] N. H. Huynh, G. Böer, H. Schramm, "Self-attention and Generative Adversarial Networks for Algae Monitoring", European Journal of Remote Sensing, doi: 10.1080/22797254.2021.2010605, 2021.

[14] G. Böer, H. Schramm, "Semantic Segmentation of Marine Species in an Unconstrained Underwater Environment", Springer Communications in Computer and Information Science 1667, Robotics, Computer Vision and Intelligent Systems, Pages 131-146, 2021.

[15] G. Böer, J. P. Gröger, S. Badri-Höher, B. Cisewski, H. Renkewitz, F. Mittermayer, T. Strickmann, and H. Schramm, "A Deep-Learning Based Pipeline for Estimating the Abundance and Size of Aquatic Organisms in an Unconstrained Underwater Environment from Continuously Captured Stereo Video", Sensors 2023, 23, 3311. https://doi.org/10.3390/s23063311, 2023.

[16] Gröger JP, Cisewski B, Badri-Hoeher S, Böer G, Boos K, Clemmesen C, Cojocaru A, Dauben V, Hoeher PA, Lehmann A, Matz S, Mehrtens H, Mittermayer F, Renkewitz H, Schramm H, Strickmann T, Westphalen J, Wilts T, Winkler J, Wolf D and Zenk O, "Development and operation of a novel non-invasive opto-acoustic underwater fish observatory in Kiel Bight, Southwestern Baltic Sea". Front. Mar. Sci. 11:1425259. doi: 10.3389/fmars.2024.

Konferenzbeiträge

[17] A. Kellner, B. Rueber, H. Schramm, "Strategies for name recognition in automatic directory assistance systems", Proc. IVTTA, Torino, Italy, Sept. 1998.

[18] A. Kellner, B. Rueber, H. Schramm, "Using combined decisions and confidence measures for name recognition in automatic directory assistance systems", Proc. ICSLP, Sydney, Australia, Vol. 7, pp. 2859 -- 2862, 1998.

[19] H. Schramm, X. Aubert, "Efficient integration of multiple pronunciations in a large vocabulary decoder", Proc. ICASSP, Istanbul, Turkey, Vol. 3, pp. 1659 -- 1662, June 2000.

[20] P. Beyerlein, X. Aubert, M. Harris, C. Meyer, H. Schramm, "Investigations on conversational speech recognition", in Proc. Eurospeech, Aalborg, Denmark, September 2001.

[21] H. Schramm, P. Beyerlein, "Towards discriminative lexicon optimization", Proc. Eurospeech, Aalborg, Denmark, September 2001.

[22] H. Schramm, P. Beyerlein, "Ideal acoustic modeling", Proc. DARPA Large Vocabulary Conversational Speech Recognition Workshop, Gaithersburg, Md., May 2001.

[23] H. Schramm, P. Beyerlein, "Discriminative optimization of the lexical model", Proc. Pronunciation Modeling and Lexicon Adaptation Workshop, Estes Park, Colorado, September 2002.

[24] H. Schramm, X. Aubert, C. Meyer, J. Peters, "Filled-pause modeling for medical transcriptions", Proc. Spontaneous Speech Processing and Recognition Workshop, Tokyo, Japan, April 2003.

[25] C. Meyer, H. Schramm, "Boosting acoustic models in large vocabulary speech recognition", Proc. IASTED Intern. Conf. on Signal and Image Processing, Honolulu, Hawaii, August 2004.

[26] H. Schramm, X. Aubert, B. Bakker, C. Meyer, H. Ney, "Modeling spontaneous speech variability in large vocabulary professional dictations", Proc. IASTED Intern. Conf. on Signal and Image Processing, Honolulu, Hawaii, August 2004.

[27] H. Schramm, O. Ecabert, J. Peters, V. Philomin, J. Weese, "Towards fully automatic 3-D object detection and segmentation", SPIE Medical Imaging, San Diego, February 2006.

[28] H. Schramm, O. Ecabert, J. Peters, V. Philomin, J. Weese, "A fully automatic 3-D object detection technique", 4-th Philips Digital Signal Processing Conference, Veldhoven, The Netherlands, November 2005.

[29] O. Ecabert, J. Peters, M. J. Walker, H. Schramm, M. Vembar, K. Subramanyan, J. von Berg, C. Lorenz, J. Weese, "Qualitative validation of automatic full heart segmentation in three-dimensional MSCT images", 1st Annual Scientific Meeting of the Society of Cardiovascular Computed Tomography, Washington DC, July 13-16, 2006.

[30] O. Ecabert, J. Peters, H. Schramm, M. Vembar, M.J. Walker, K. Subramanyan, J. Weese, "Modeling inter-individual and inter-phase shape variability for model-based segmentation of cardiac MSCT images", 1st Annual Scientific Meeting of the Society of Cardiovascular Computed Tomography, Washington DC, July 13-16, 2006.

[31] O. Ecabert, J. Peters, H. Schramm, M. Vembar, M. J. Walker, K. Subramanyan, J. von Berg, C. Lorenz, J. Weese, "Automatic segmentation of 3-D MSCT images for cardiac functional analysis", RSNA 2006 (Congress of the Radiological Society of North America).

[32] O. Ecabert, M. J. Walker, J. Peters, H. Schramm, M. Vembar, K. Subramanyan, J. von Berg, C. Lorenz, J. Weese, "Automatic localization of landmarks for standardized display of cardiac images", RSNA 2006 (Congress of the Radiological Society of North America).

[33] J. Peters, O. Ecabert, C. Meyer, H. Schramm, R. Kneser, A. Groth, J. Weese, "Automatic Whole Heart Segmentation in Static Magnetic Resonance Image Volumes", Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007, 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part II 2007.

[34] A.-B. Martin-Recuero, P. Beyerlein, H. Schramm, "Discriminative Optimization of 3-D Shape Models for the Generalized Hough Transform", 7th International Conference and Workshop on Ambient Intelligence and Embedded Systems, Sept. 2008.

[35] H. Ruppertshofen, C. Lorenz, P. Beyerlein, Z. Salah, G. Rose, H. Schramm, "Fully Automatic Model Creation for Object Localization Utilizing the Generalized Hough Transform", Bildverarbeitung für die Medizin (BVM) (281-285), 2010.

[36] H. Ruppertshofen, C. Lorenz, P. Beyerlein, Z. Salah, G. Rose, H. Schramm, "Lokalisierung der Leber mittels einer diskriminativen Generalisierten Hough Transformation", Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC), November 2010.

[37] H. Ruppertshofen, C. Lorenz, P. Beyerlein, Z. Salah, G. Rose, H. Schramm, “Iterative Training of Discriminative Models for the Generalized Hough Transform”, Workshop on Medical Computer Vision: Recognition Techniques and Applications in Medical Images, Peking, 2010.

[38] H. Ruppertshofen, C. Lorenz, P. Beyerlein, Z. Salah, G. Rose, H. Schramm, “Shape Model Training for Concurrent Localization of the Left and Right Knee”, SPIE Medical Imaging Conference, Florida, 2011. Poster Award

[39] M. Brunk, H. Ruppertshofen, S. Schmidt, P. Beyerlein, H. Schramm, “Bone Age Classification Using the Discriminative Generalized Hough Transform”, BVM (Bildverarbeitung für die Medizin) 2011.

[40] H. Ruppertshofen, C. Lorenz, P. Beyerlein, Z. Salah, G. Rose, H. Schramm, "Multi-Level Approach for the Discriminative Generalized Hough Transform", Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC), November 2011.

[41] M. Harmsen, B. Fischer, H. Schramm, T. M. Deserno, "Support Vector Machine Classification using Correlation Prototypes for Bone Age Assessment", BVM (Bildverarbeitung für die Medizin) 2012.

[42] F. Boero, H. Ruppertshofen, H. Schramm, "Femur Localization Using the Discriminative Generalized Hough Transform", BVM (Bildverarbeitung für die Medizin), Berlin, 2012.

[43] H. Ruppertshofen, C. Lorenz, P. Beyerlein, Z. Salah, G. Rose, H. Schramm, "A multidimensional model for localization of highly variable objects", SPIE Medical Imaging Conference, San Diego, 2012.

[44] F. Hahmann, H. Ruppertshofen, G. Böer, R. Stannarius, H. Schramm, “Eye Localization Using the Discriminative Generalized Hough Transform”, DAGM 2012, Graz.

[45] F. Hahmann, H. Ruppertshofen, G. Böer, H. Schramm, “Model Interpolation for Eye Localization Using the Discriminative Generalized Hough Transform”, BioSig, Darmstadt 2012.

[46] M. Harmsen, B. Fischer, H. Schramm, T. Seidel, T. M. Deserno, “Support vector machine classification supported by cross-correlation applied to bone age assessment“, SPIE Medical Imaging Conference, Florida, 2013.

[47] D. Haak, J. Yu, H. Simon, H. Schramm, T. Seidl, T. M. Deserno, “Bone age assessment using support vector regression with smart class mapping”, SPIE Medical Imaging Conference, Florida, 2013.

[48] F. Hahmann, G. Böer, H. Schramm, “Bone Age Assessment Using the Classifying Generalized Hough Transform“, submitted to GCPR 2013.

[49] F. Hahmann, G. Böer, H. Schramm, “Combination of Facial Landmarks for Robust Eye Localization Using the Discriminative Generalized Hough Transform“, BioSig, Darmstadt, Germany, 2013.

[50] H. Essig, G. Boeer, I. Buhr, N.-C. Gellrich, H. Schramm, "Automatisierte Detektion von kephalometrischen Landmarken auf dreidimensionalen Oberflächennetzen", IPJ International Poster Journal of Dentistry and Oral Medicine, 2014.

[51] F. Hahmann, G. Böer, T. Deserno, H. Schramm , "Epiphyses Localization for Bone Age Assessment Using the Discriminative Generalized Hough Transform", Bildverarbeitung für die Medizin, Aachen, Germany, 2014.

[52] G. Böer, F. Hahmann, I. Buhr, H. Essig, H. Schramm, "Detection of Facial Landmarks in 3D Face Scans Using the Discriminative Generalized Hough Transform (DGHT)", in Bildverarbeitung für die Medizin, Lübeck, Germany, 2015.

[53] F. Hahmann, G. Boeer, E. Gabriel, H. Schramm, "A Shape Consistency Measure for Improving the Generalized Hough Transform", Conference on Computer Vision Theory and Applications (VISAPP), Berlin, Germany, 2015.

[54] F. Hahmann, G. Böer, E. Gabriel, T. M. Deserno, C. Meyer, H. Schramm, "Classification of Voting Patterns to Improve the Generalized Hough Transform for Epiphyses Localization", SPIE Medical Imaging, San Diego, 2016.

[55] A. O. Mader, H. Schramm, C. Meyer, "Using web images as additional training resource for the Discriminative Generalized Hough Transform", Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA), Oulu, Finland, 2016.

[56] E. Gabriel, F. Hahmann, G. Boeer, H. Schramm, C. Meyer, "Structured Edge Detection for Improved Object Localization using the Discriminative Generalized Hough Transform", International Conference on Computer Vision Theory and Applications (VISAPP), Rome, Italy, 2016.

[57] E. Gabriel, H. Schramm, C. Meyer, "Experiments on Pedestrian Localization Using the Discriminative Generalized Hough Transform", International Symposium on Ambient Intelligence and Embedded Systems, 2016.

[58] A. O. Mader, H. Schramm, C. Meyer, "Eﬃcient Epiphyses Localization Using Regression Tree Ensembles and a Conditional Random Field", in Bildverarbeitung für die Medizin, Heidelberg, Germany, 2017.

[59] E. Gabriel, H. Schramm, C. Meyer, "Analysis of the Discriminative Generalized Hough Transform for Pedestrian Detection", International Conference on Image Analysis and Processing (ICIAP), Catania, Italy, 2017.

[60] A. O. Mader, J. von Berg, M. Bergtholdt, J. Modersitzky, H. Schramm, C. Meyer, "Detection and Localization of Landmarks in the Lower Extremities Using an Automatically Learned Conditional Random Field", International Workshop on Graphs in Biomedical Image Analysis (GRAIL), 2017, Quebec, Canada. Best Paper Award

[61] E. Gabriel, H. Schramm, C. Meyer, "The Discriminative Generalized Hough Transform as a Proposal Generator for a Deep Network in Automatic Pedestrian Localization", International Conference on Computer Vision Theory and Applications, VISAPP, 2018.

[62] G. Böer, R. Veeramalli, H. Schramm, "Segmentation of Fish in Realistic Underwater Scenes using Lightweight Deep Learning Models", Int. Conf. on Robotics, Computer Vision and Intelligent Systems - ROBOVIS, pages 158-164, 2021.

[63] D. Laufs, H. Dankowski, H. Schramm, O. Landsiedel, D. Nowotka, D. Sommerstedt, "CAPTN Förde Areal – A Smart and Clean Technology Platform for the Testing and Development of Future Autonomous Passenger Ferries", in AIS: Autonomous Inland & Short Sea Shipping, 2021.

Patente

[1] B. Rueber, A. Kellner, H. Schramm, "Method for error recovery in method and device for recognising a user presentation through assessing the reliability of a limited set of hypotheses", Pub. No. WO/2000/016311, Pub. Date 23.03.2000.

[2] H. Schramm, “Method and system for automated control of actions in presentations”, EP 1220201 B1, 2001.

[3] H. Schramm, P. Beyerlein, "Verfahren und System zum Training von jeweils genau einer Realisierungsvariante eines Inventarmusters zugeordneten Parametern eines Mustererkennungssystems", Deutsche Patentanmeldung 10119284A1, 2001.

[4] H. Schramm, “Training the parameters of a speech recognition system for the recognition of pronunciation variations”, EP 1251489 A2, 2002.

[5] H. Schramm, "System and method for sales promotion", Pub. No. WO/2002/103589, Pub. Date 27.12.2003.

[6] H. Schramm, "Portable electronic device having means for registering its arrangement in space", Pub. No. WO/2003/077087, Pub. Date 18.09.2003.

[7] H. Schramm, "Configurable control of a mobile device by means of movement patterns", Pub. No. WO/2004/082248, Pub. Date 23.09.2004.

[8] H. Schramm, "Error detection for speech to text transcription systems”, Pub. No. WO/2005/045803, Pub. Date . 19.05.2005.

[9] H. Schramm, "Automatic 3-D object detection", Pub. No. WO/2007/072391, Pub. Date 28.06.2007.

[10] J. von Berg, O. Ecabert, C. Lorenz, J. Peters, H. Schramm, J Weese, „Progressive model-based adaptation”, EP2143072 A2, 2008.

[11] H. Schramm, G. Kiefer, "Locally optimized transfer functions for volume visualization", Pub. No. WO/2008/007334, Pub. Date 17.01.2008.

[12] G. Kiefer, H. Lehmann, D. Geller, H. Schramm, J. Peters, O. Ecabert, J. Weese, "Anatomy-related image-context-dependent applications for efficient diagnosis", Pub. No. WO/2008/018014, Pub. Date 14.02.2008.

[13] J. Peters, O. Ecabert, H. Schramm, J. Weese, „Flexible Plug-And-Play Medical Image Segmentation“,WO Patent 2.009.034.499, 2009.

[14] H. Schramm, "Werkstück zum Erlernen der Handhabung von Werkzeugen und Verfahren zu dessen Herstellung", Deutsche Patentanmeldung 102008045188, 2009.

[15] H. Schramm, "Verfahren zum Erstellen eines Blocks, in dessen Inneren wenigstens ein sich farblich absetzendes Objekt eingebettet ist.", EP2404503B1, 2010.

[16] H. Schramm, H. Ruppertshofen, "Klassifikation mittels Diskriminativer Generalisierter Hough Transformation", Deutsche Patentanmeldung 10 2011 014 171, 2011.

[17] J. Gröger, S. Badri-Höher, H. Schramm, L. Wolff, G. Böer, "Vorrichtung und Verfahren zur Datenanalyse", Deutsche Patentanmeldung 102018217163A1, 2018.