My Talks & Publications
In this paper we propose a machine learning-based approach to predict a multitude of insurance claim categories related to canine diseases. We introduce several machine learning approaches that are evaluated on a pet insurance dataset consisting of 785,565 dogs from the US and Canada whose insurance claims have been recorded over 17 years.
Monitoring the activities of daily living (ADLs) and detection of deviations from previous patterns is crucial to assessing the ability of an elderly person to live independently in their community and in early detection of upcoming critical situations. In this paper we propose a new framework for reliable ADL recognition that is validated by experimental setups in smart home installations.
The 2013 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic use of hyperspectral and Light Detection And Ranging (LiDAR) data. This paper highlights the two awarded research contributions, which investigated different approaches for the fusion of hyperspectral and LiDAR data, including a combined unsupervised and supervised classification scheme, and a graph-based method for the fusion of spectral, spatial, and elevation information.
Talks
“Panel Discussion: AI Trends”, The Frankfurt AI Conference, October 2024
“Explainable AI with Real-Life Applications”, Helmholtz Summer School, September 2024
“Predicting health outcomes in dogs using insurance claims data”, AI Meetup Frankfurt, April 2024
“How Care-Connect and SPRYFOX use NLP in making patient-level decisions”, NLP Summit, April 2024
“Explainable AI - How explainable AI models lead to more transparency and trust in HR decision making”, HR Digital, Munich, November 2023
“How AI leverages insurance claims to predict diseases in humankind’s best friend”, Big Data & AI, Frankfurt, May 2023
Patents
“Techniques for predicting diseases using simulations improved via machine learning”, US20230154623A1 and CA3181860A1
“Techniques for disease prediction using machine learning-improved simulations and for generating display elements using simulation results”, US20230376860A1
“Motion Matching Analysis”, US11282214B2
Journal Papers
C. Debes, J. Wowra, S. Manzoor and A. Ruple, “Predicting health outcomes in dogs using insurance claims data”, Nature Scientific Reports, Vol 13, No 9122, 2023
S. Sukhanov, R. Wu, C. Debes and A. M. Zoubir, “Dynamic pattern matching with multiple queries on large scale data streams”, Elsevier Signal Processing, Vol 121, 2020
C. Debes, A. Merentitis, S. Sukhanov, M. Niessen, N. Frangiadakis and A. Bauer, “Monitoring activities of daily living in smart homes: Understanding human behavior”, IEEE Signal Processing Magazine, Vol. 33, No. 2, pp. 81-94, 2016
A. Merentitis and C. Debes, “Many hands make light work - On Ensemble Learning Techniques for Data Fusion in Remote Sensing”, IEEE Geoscience and Remote Sensing Magazine, Vol. 3, 86-99, 2015
C. Debes et al “Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 7, Issue 6, 2405-2418, 2014
A. Merentitis, C. Debes and R. Heremans, “Ensemble Learning in Hyperspectral Image Classification: Towards Selecting a Favorable Bias-Variance Tradeoff”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 7, Issue 4, 1089-1102, 2014
J. Hahn, C. Debes, M. Leigsnering and A.M. Zoubir ,"Compressive Sensing and Adaptive Direct Sampling in Hyperspectral Imaging" , Digital Signal Processing, Vol 26, 113-126, 2014
R. Fandos, C. Debes and A. M. Zoubir ,"Resampling methods for quality assessment of classifier performance and optimal number of features" , Signal Processing, Vol. 93, Issue 11, 2956-2968, 2013
F. Yin, C. Debes and A. M. Zoubir ,"Parametric Waveform Design using Discrete Prolate Spheroidal Sequences for Enhanced Detection of Extended Targets" , IEEE Transactions on Signal Processing 60(9):4525-4536 , 2012
A. A. Mostafa, C. Debes and A. M. Zoubir ,"Segmentation by Classification for Through-the-Wall Radar Imaging Using Polarization Signatures" , IEEE Transactions on Geoscience and Remote Sensing 50(9):3425 - 3439 , 2012
C. Debes, A.M. Zoubir and M. G. Amin ,"Enhanced Detection using Target Polarization Signatures in Through-the-Wall Radar Imaging" , IEEE Transactions on Geoscience and Remote Sensing 50(5 part:2) , 2012
C. Debes, J. Hahn, A. M. Zoubir and M. G. Amin ,"Target Discrimination and Classification in Through-the-Wall Radar Imaging" , IEEE Transactions on Signal Processing 59(10):4664 -4676 2011
C. Debes, J. Riedler, A. M. Zoubir and M. G. Amin ,"Adaptive Target Detection with application to Through-the-Wall Radar Imaging" , IEEE Transactions on Signal Processing 58(11):5572--5583 , 2010
C. Debes, M. G. Amin and A. M. Zoubir ,"Target detection in Single- and Multiple-View Through-the-Wall Radar Imaging" , IEEE Transactions on Geoscience and Remote Sensing 47(5):1349-1361, 2009
Book Chapter
C. Debes and A.M. Zoubir ,"Through-the-Wall Radar Imaging" ,In M. G. Amin, editor, Chapter Detection approaches in Through-Wall Radar Imaging, Publisher: CRC Press, December 2010
Conference Papers
S. Sukhanov, C. Debes, A. M. Zoubir, “Dynamic selection of classifiers for fusing imbalanced heterogeneous data”, Proc. of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), page 5361-5365, 2019
R. Wu, S. Sukhanov, C. Debes, “Real Time Pattern Matching with Dynamic Normalization”, arxviv.1912.11977, 2019
S. Sukhanov, A. Merentitis, C. Debes, J. Hahn and A. M. Zoubir, "Combining SVMS for Classification on Class Imbalanced Data," IEEE Statistical Signal Processing Workshop (SSP), Freiburg im Breisgau, Germany, 2018, pp. 90-94, 2018
S. Sukhanov, C. Debes and A. M. Zoubir, "Interpretable Clustering Ensembles Using Binary Matrix Factorization," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, Canada, 2018, pp. 4229-4233, 2018
S. Sukhanov, D. Budylskii, I. Tankoyeu, R. Heremans and C. Debes, "Fusion of Lidar, Hyperspectral and RGB Data for Urban Land Use and Land Cover Classification," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, pp. 3864-3867, 2018
S. Sukhanov, V. Gupta, C. Debes and A. M. Zoubir, "Consensus clustering on data fragments," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA, pp. 4631-4635, 2017
S. Sukhanov, I. Tankoyeu, J. Louradour, R. Heremans, D. Trofimova and C. Debes, "Multilevel ensembling for local climate zones classification," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 2017
S Sukhanov, A Merentitis, C Debes, J Hahn, AM Zoubir, “Bootstrap-based SVM aggregation for class imbalance problems”, European Signal Processing Conference (EUSIPCO), page 165 - 169, 2015
A. Merentitis and C. Debes, "Automatic fusion and classification using random forests and features extracted with deep learning," 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 2015, pp. 2943-2946,
N. Thakre, C. Debes, R. Heremans and A. M. Zoubir ,"Anomaly Detection for Dike Monitoring using System Identification" , IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), page 399-403, 2014
C. Debes, C. Weiss and A. M. Zoubir ,"How Good is Your Super-Resolution Image? Quality Assurance in Image Reconstruction Using the Bootstrap", IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pg. 5959-5963, 2013
C. Debes, S. Leier, F. Nikolay and A. M. Zoubir ,"Compressive Sensing for Synthetic Aperture Imaging using a sparse basis transform", Proc. of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Munich, Germany, pg. 7420-7423, 2012
F. Yin, C. Debes and A.M. Zoubir ,"Parametric Waveform Design for Improved Target Detection", In Proc. European Signal Processing Conference (EUSIPCO) , page 2074-2078, 2011
C. Debes, A.M. Zoubir and M.G. Amin ,"Detection of geometrically known targets in Through-the-Wall Radar Imaging" , Proc. of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), page 3624-3627, 2011
M. Leigsnering, C. Debes and A.M. Zoubir ,"Compressive Sensing in Through-the-Wall Radar Imaging" , Proc. of the 36th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), page 3008-4011, 2011
C. Debes, C. Weiss, A.M. Zoubir and M.G. Amin ,"Wall-Clutter Mitigation using Cross-Beamforming in Through-the-Wall Radar Imaging" , Proc. of the 18th European Signal Processing Conference (EUSIPCO) , page 1097-1100, 2010
C. Debes, C. Weiss, A. Zoubir and M. Amin ,"Distributed Detection in Through-the-Wall Radar Imaging using the Bootstrap" , Proc. of the 35th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , page 3530-3533, 2010
C. Debes, J. Hahn, A.M. Zoubir and M.G. Amin ,"Feature Extraction in Through-the-Wall Radar Imaging" , Proc. of the 35th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , page 3562-3565, 2010
C. Debes, M. Amin and A.M. Zoubir ,"Optimal Decision Fusion in Through-the-wall Radar Imaging" , Proc. of the IEEE International Workshop on Statistical Signal Processing (SSP) , page 761-764. Cardiff, Wales, UK, 2009
C. Debes, R. Engel, A. Zoubir and A. Kraft ,"Quality Assessment of Synthetic Aperture Sonar Images" , Proc. of the 2009 IEEE OCEANS conference, Bremen, Germany , page 1-4, 2009
C. Debes, J. Riedler, M. Amin and A. Zoubir ,"Iterative Target Detection Approach for Through-the-Wall Radar Imaging" , Proc. of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , page 3061 - 3064. Taipei, Taiwan, 2009
C. Debes, M.G. Amin and A.M. Zoubir ,"Target Detection in Multiple-Viewing Through-the-Wall Radar Imaging" , Proc. of the 28th IEEE International Geoscience &Remote Sensing Symposium (IGARSS) , page 173-176. Boston, MA, USA, 2008
C. Debes and A. M. Zoubir ,"The Recursive Maximum Likelihood Algorithm for Non-Stationary Signals" , Proc. of the 33rd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , page 3777 - 3780. Las Vegas, NV, USA, 2008
C. Debes and A. M. Zoubir ,"Bootstrapping Autoregressive Plus Noise Processes" , Proceedings of the 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) , page 53-56. St. Thomas, US Virgin Islands, USA, 2007
C. Debes, T. Wedi, C. L. Brown and A. M. Zoubir ,"Motion Estimation using a Joint Optimisation of the Motion Vector Field and a Super-Resolution Reference Image" , Proceedings of the 14th IEEE International Conference on Image Processing (ICIP) , page 497-500. San Antonio, TX, USA, 2007
C.L. Brown, R.F. Brcich and C. Debes ,"Adaptive M-estimators for use in structured and unstructured robust covariance estimation" , Proceedings of the 13th IEEE Workshop on Statistical Signal Processing (SSP) , page 573-578. Bordeaux, France, 2005
Theses
C. Debes ,"Advances in Detection and Classification for Through-the-Wall Radar Imaging" Phd thesis, 2010
C. Debes, “High-Precision Motion Estimation in Video Sequences Considering Disturbing Factors”, Master Thesis, 2006
C. Debes, “On the Robust Estimation of Scale”, Bachelor Thesis, 2004