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Scalable real-time parking lot classification: An evaluation of image features and supervised learning algorithmsTschentscher, M., Koch, C., König, M., Salmen, J., & Schlipsing, M.In Proceedings of the IEEE International Joint Conference on Neural Networks
@inproceedings{TschentscherKochKönigEtAl2015, author = {Tschentscher, M. and Koch, C. and König, M. and Salmen, J. and Schlipsing, M.}, title = {Scalable real-time parking lot classification: An evaluation of image features and supervised learning algorithms}, booktitle = {Proceedings of the IEEE International Joint Conference on Neural Networks}, year = {2015}, }Tschentscher, M., Koch, C., König, M., Salmen, J., & Schlipsing, M.. (2015). Scalable real-time parking lot classification: An evaluation of image features and supervised learning algorithms. In Proceedings of the IEEE International Joint Conference on Neural Networks.2014
Adaptive pattern recognition in real-time video-based soccer analysisSchlipsing, M., Salmen, J., Tschentscher, M., & Igel, C.Journal of Real-Time Image Processing, 1–17@article{SchlipsingSalmenTschentscherEtAl2014, author = {Schlipsing, Marc and Salmen, Jan and Tschentscher, Marc and Igel, Christian}, title = {Adaptive pattern recognition in real-time video-based soccer analysis}, journal = {Journal of Real-Time Image Processing}, pages = {1–17}, year = {2014}, }Schlipsing, M., Salmen, J., Tschentscher, M., & Igel, C. (2014). Adaptive pattern recognition in real-time video-based soccer analysis. Journal of Real-Time Image Processing, 1–17.2013
Video-based trailer detection and articulation estimationCaup, L., Salmen, J., Muharemovic, I., & Houben, S.In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 1179–1184)@inproceedings{CaupSalmenMuharemovicEtAl2013, author = {Caup, Lukas and Salmen, Jan and Muharemovic, Ibro and Houben, Sebastian}, title = {Video-based trailer detection and articulation estimation}, booktitle = {Proceedings of the IEEE Intelligent Vehicles Symposium (IV)}, pages = {1179–1184}, year = {2013}, }Caup, L., Salmen, J., Muharemovic, I., & Houben, S.. (2013). Video-based trailer detection and articulation estimation. In Proceedings of the IEEE Intelligent Vehicles Symposium (IV) (pp. 1179–1184).Detection of traffic signs in real-world images: The German Traffic Sign Detection BenchmarkHouben, S., Stallkamp, J., Salmen, J., Schlipsing, M., & Igel, C.In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN) (pp. 1–8)@inproceedings{HoubenStallkampSalmenEtAl2013, author = {Houben, Sebastian and Stallkamp, Johannes and Salmen, Jan and Schlipsing, Marc and Igel, Christian}, title = {Detection of traffic signs in real-world images: The German Traffic Sign Detection Benchmark}, booktitle = {Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN)}, pages = {1–8}, year = {2013}, }Houben, S., Stallkamp, J., Salmen, J., Schlipsing, M., & Igel, C. (2013). Detection of traffic signs in real-world images: The German Traffic Sign Detection Benchmark. In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN) (pp. 1–8).Autonomous Driving in a Parking Garage: Vehicle Localization and Tracking Using Environment-embedded LIDAR SensorsIbisch, A., Stümper, S., Altinger, H., Neuhausen, M., Tschentscher, M., Schlipsing, M., et al.In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 829–934)@inproceedings{IbischStümperAltingerEtAl2013, author = {Ibisch, A. and Stümper, S. and Altinger, H. and Neuhausen, M. and Tschentscher, M. and Schlipsing, M. and Salmen, J. and Knoll, A.}, title = {Autonomous Driving in a Parking Garage: Vehicle Localization and Tracking Using Environment-embedded LIDAR Sensors}, booktitle = {Proceedings of the IEEE Intelligent Vehicles Symposium}, pages = {829–934}, year = {2013}, }Ibisch, A., Stümper, S., Altinger, H., Neuhausen, M., Tschentscher, M., Schlipsing, M., et al. (2013). Autonomous Driving in a Parking Garage: Vehicle Localization and Tracking Using Environment-embedded LIDAR Sensors. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 829–934).Real-Time Stereo Vision: Optimizing Semi-Global MatchingMichael, M., Salmen, J., Stallkamp, J., & Schlipsing, M.In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 1197–1202)@inproceedings{MichaelSalmenStallkampEtAl2013, author = {Michael, M. and Salmen, J. and Stallkamp, J. and Schlipsing, M.}, title = {Real-Time Stereo Vision: Optimizing Semi-Global Matching}, booktitle = {Proceedings of the IEEE Intelligent Vehicles Symposium}, pages = {1197–1202}, year = {2013}, }Michael, M., Salmen, J., Stallkamp, J., & Schlipsing, M.. (2013). Real-Time Stereo Vision: Optimizing Semi-Global Matching. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 1197–1202).Eine Systemarchitektur für effiziente videobasierte FahrerassistenzsystemeSalmen, J.Doctoral thesis, Ruhr-Universität Bochum@phdthesis{Salmen2013, author = {Salmen, Jan}, title = {Eine Systemarchitektur für effiziente videobasierte Fahrerassistenzsysteme}, school = {Ruhr-Universität Bochum}, year = {2013}, }Salmen, J. (2013). Eine Systemarchitektur für effiziente videobasierte Fahrerassistenzsysteme. Doctoral thesis, Ruhr-Universität Bochum.Echtzeit-Videoanalyse im FußballSchlipsing, M., Salmen, J., & Igel, C.KI - Künstliche Intelligenz, 27(3), 235–240@article{SchlipsingSalmenIgel2013, author = {Schlipsing, Marc and Salmen, Jan and Igel, Christian}, title = {Echtzeit-Videoanalyse im Fußball}, journal = {KI - Künstliche Intelligenz}, volume = {27}, number = {3}, pages = {235–240}, year = {2013}, }Schlipsing, M., Salmen, J., & Igel, C. (2013). Echtzeit-Videoanalyse im Fußball. KI - Künstliche Intelligenz, 27(3), 235–240.Comparing Image Features and Machine Learning Algorithms for Real-time Parking-space ClassifiactionTschentscher, M., Neuhausen, M., Koch, C., König, M., Salmen, J., & Schlipsing, M.In Proceedings of the ASCE International Workshop on Computing in Civil Engineering (pp. 363–370)@inproceedings{TschentscherNeuhausenKochEtAl2013, author = {Tschentscher, M. and Neuhausen, M. and Koch, C. and König, M. and Salmen, J. and Schlipsing, M.}, title = {Comparing Image Features and Machine Learning Algorithms for Real-time Parking-space Classifiaction}, booktitle = {Proceedings of the ASCE International Workshop on Computing in Civil Engineering}, pages = {363–370}, year = {2013}, }Tschentscher, M., Neuhausen, M., Koch, C., König, M., Salmen, J., & Schlipsing, M.. (2013). Comparing Image Features and Machine Learning Algorithms for Real-time Parking-space Classifiaction. In Proceedings of the ASCE International Workshop on Computing in Civil Engineering (pp. 363–370).2012
Google street view images support the development of vision-based driver assistance systemsSalmen, J., Houben, S., & Schlipsing, M.In Proceedings of the Intelligent Vehicles Symposium (IV), 2012 IEEE (pp. 891–895) IEEE@inproceedings{SalmenHoubenSchlipsing2012, author = {Salmen, Jan and Houben, Sebastian and Schlipsing, Marc}, title = {Google street view images support the development of vision-based driver assistance systems}, booktitle = {Proceedings of the Intelligent Vehicles Symposium (IV), 2012 IEEE}, pages = {891–895}, organization = {IEEE}, year = {2012}, }Salmen, J., Houben, S., & Schlipsing, M.. (2012). Google street view images support the development of vision-based driver assistance systems. In Proceedings of the Intelligent Vehicles Symposium (IV), 2012 IEEE (pp. 891–895). IEEE.Roll Angle Estimation for Motorcycles: Comparing Video and Inertial Sensor ApproachesSchlipsing, M., Salmen, J., Lattke, B., Schröter, K., & Winner, H.In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 500–505)@inproceedings{SchlipsingSalmenLattkeEtAl2012, author = {Schlipsing, M. and Salmen, J. and Lattke, B. and Schröter, K. and Winner, H.}, title = {Roll Angle Estimation for Motorcycles: Comparing Video and Inertial Sensor Approaches}, booktitle = {Proceedings of the IEEE Intelligent Vehicles Symposium}, pages = {500–505}, year = {2012}, }Schlipsing, M., Salmen, J., Lattke, B., Schröter, K., & Winner, H. (2012). Roll Angle Estimation for Motorcycles: Comparing Video and Inertial Sensor Approaches. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 500–505).Man vs. Computer: Benchmarking Machine Learning Algorithms for Traffic Sign RecognitionStallkamp, J., Schlipsing, M., Salmen, J., & Igel, C.Neural Networks, 32, 323–332@article{StallkampSchlipsingSalmenEtAl2012, author = {Stallkamp, J. and Schlipsing, M. and Salmen, J. and Igel, C.}, title = {Man vs. Computer: Benchmarking Machine Learning Algorithms for Traffic Sign Recognition}, journal = {Neural Networks}, volume = {32}, pages = {323–332}, year = {2012}, }Stallkamp, J., Schlipsing, M., Salmen, J., & Igel, C. (2012). Man vs. Computer: Benchmarking Machine Learning Algorithms for Traffic Sign Recognition. Neural Networks, 32, 323–332.2011
Real-time estimation of optical flow based on optimized Haar wavelet featuresSalmen, J., Caup, L., & Igel, C.In Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization (pp. 448–461)@inproceedings{SalmenCaupIgel2011, author = {Salmen, J. and Caup, L. and Igel, C.}, title = {Real-time estimation of optical flow based on optimized Haar wavelet features}, booktitle = {Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization}, pages = {448–461}, year = {2011}, }Salmen, J., Caup, L., & Igel, C. (2011). Real-time estimation of optical flow based on optimized Haar wavelet features. In Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization (pp. 448–461).Video-Based Roll Angle Estimation for Two-Wheeled VehiclesSchlipsing, M., Schepanek, J., & Salmen, J.In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 876–881)@inproceedings{SchlipsingSchepanekSalmen2011, author = {Schlipsing, M. and Schepanek, J. and Salmen, J.}, title = {Video-Based Roll Angle Estimation for Two-Wheeled Vehicles}, booktitle = {Proceedings of the IEEE Intelligent Vehicles Symposium}, pages = {876–881}, year = {2011}, }Schlipsing, M., Schepanek, J., & Salmen, J.. (2011). Video-Based Roll Angle Estimation for Two-Wheeled Vehicles. In Proceedings of the IEEE Intelligent Vehicles Symposium (pp. 876–881).The German Traffic Sign Recognition Benchmark: A multi-class classification competitionStallkamp, J., Schlipsing, M., Salmen, J., & Igel, C.In Proceedings of the IEEE International Joint Conference on Neural Networks (pp. 1453–1460)@inproceedings{StallkampSchlipsingSalmenEtAl2011, author = {Stallkamp, J. and Schlipsing, M. and Salmen, J. and Igel, C.}, title = {The German Traffic Sign Recognition Benchmark: A multi-class classification competition}, booktitle = {Proceedings of the IEEE International Joint Conference on Neural Networks}, pages = {1453–1460}, year = {2011}, }Stallkamp, J., Schlipsing, M., Salmen, J., & Igel, C. (2011). The German Traffic Sign Recognition Benchmark: A multi-class classification competition. In Proceedings of the IEEE International Joint Conference on Neural Networks (pp. 1453–1460).2010
Efficient Update of the Covariance Matrix Inverse in Iterated Linear Discriminant AnalysisSalmen, J., Schlipsing, M., & Igel, C.Pattern Recognition Letters, 31, 1903–1907@article{SalmenSchlipsingIgel2010, author = {Salmen, J. and Schlipsing, M. and Igel, C.}, title = {Efficient Update of the Covariance Matrix Inverse in Iterated Linear Discriminant Analysis}, journal = {Pattern Recognition Letters}, volume = {31}, pages = {1903–1907}, year = {2010}, }Salmen, J., Schlipsing, M., & Igel, C. (2010). Efficient Update of the Covariance Matrix Inverse in Iterated Linear Discriminant Analysis. Pattern Recognition Letters, 31, 1903–1907.2009
Real-Time Stereo Vision: Making more out of Dynamic ProgrammingSalmen, J., Schlipsing, M., Edelbrunner, J., Hegemann, S., & Lueke, S.In Proceedings of the International Conference on Computer Analysis of Images and Patterns (pp. 1096–1103)@inproceedings{SalmenSchlipsingEdelbrunnerEtAl2009, author = {Salmen, J. and Schlipsing, M. and Edelbrunner, J. and Hegemann, S. and Lueke, S.}, title = {Real-Time Stereo Vision: Making more out of Dynamic Programming}, booktitle = {Proceedings of the International Conference on Computer Analysis of Images and Patterns}, pages = {1096–1103}, year = {2009}, }Salmen, J., Schlipsing, M., Edelbrunner, J., Hegemann, S., & Lueke, S. (2009). Real-Time Stereo Vision: Making more out of Dynamic Programming. In Proceedings of the International Conference on Computer Analysis of Images and Patterns (pp. 1096–1103).2007
Evolutionary Optimization of Wavelet Feature Sets for Real-Time Pedestrian ClassificationSalmen, J., Suttorp, T., Edelbrunner, J., & Igel, C.In Proceedings of the IEEE Conference on Hybrid Intelligent Systems (pp. 222–227)@inproceedings{SalmenSuttorpEdelbrunnerEtAl2007, author = {Salmen, J. and Suttorp, T. and Edelbrunner, J. and Igel, C.}, title = {Evolutionary Optimization of Wavelet Feature Sets for Real-Time Pedestrian Classification}, booktitle = {Proceedings of the IEEE Conference on Hybrid Intelligent Systems}, pages = {222–227}, year = {2007}, }Salmen, J., Suttorp, T., Edelbrunner, J., & Igel, C. (2007). Evolutionary Optimization of Wavelet Feature Sets for Real-Time Pedestrian Classification. In Proceedings of the IEEE Conference on Hybrid Intelligent Systems (pp. 222–227).The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.
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