1. Quentin Massoz. Non-invasive, automatic, and real-time characterization of drowsiness based on eye closure dynamics. PhD thesis, University of Liège, Belgium, April 2019. Keyword(s): Drowsiness, Driver monitoring, Face, Eye closure, Pyschomotor vigilance test, Reaction time, CNN, Deep learning.
   

   @phdthesis{Massoz2019NonInvasive,
   title = {Non-invasive, automatic, and real-time characterization of drowsiness based on eye closure dynamics},
   author = {Massoz, Quentin},
   school = {University of Li\`ege, Belgium},
   keywords = {Drowsiness, Driver monitoring, Face, Eye closure, Pyschomotor vigilance test, Reaction time, CNN, Deep learning},
   year = {2019},
   month = {April},
   url = {https://hdl.handle.net/2268/233355} 
   }
   

1. Vincent Pierlot and Marc Van Droogenbroeck. Statistical analysis of modulated codes for robot positioning: application to BeAMS. TechRxiv, 11:1-55, 2019. Keyword(s): Angle, Angle measurement, Estimator, Mean, Variance, Probability density function, Mobile robot, Beacon, BeAMS, Code, Statistics, Positioning, Triangulation, Infrared signal, Code modulation, On-off keying.
   

   @article{Pierlot2019Statistical,
   title = {Statistical analysis of modulated codes for robot positioning: application to {BeAMS}},
   author = {Pierlot, Vincent and {Van Droogenbroeck}, Marc},
   journal = {TechRxiv},
   year = {2019},
   volume = {11},
   pages = {1-55},
   keywords = {Angle, Angle measurement, Estimator, Mean, Variance, Probability density function, Mobile robot, Beacon, BeAMS, Code, Statistics, Positioning, Triangulation, Infrared signal, Code modulation, On-off keying},
   doi = {10.36227/techrxiv.10303526.v1},
   url = {http://doi.org/10.36227/techrxiv.10303526.v1} 
   }
   

1. Anthony Cioppa, Adrien Deliège, Maxime Istasse, Christophe De Vleeschouwer, and Marc Van Droogenbroeck. ARTHuS: Adaptive Real-Time Human Segmentation in Sports through Online Distillation. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports, Long Beach, California, USA, pages 2505-2514, June 2019. Note: Best CVsports paper award. Keyword(s): Soccer, Semantic segmentation, Artificial intelligence, Machine learning, Deep learning, CNN, DeepSport, Best paper award.
   

   @inproceedings{Cioppa2019ARTHuS,
   title = {{ARTHuS}: Adaptive Real-Time Human Segmentation in Sports through Online Distillation},
   author = {Cioppa, Anthony and Deli\`ege, Adrien and Istasse, Maxime and De Vleeschouwer, Christophe and {Van Droogenbroeck}, Marc},
   booktitle = {IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports},
   pages = {2505-2514},
   month = {June},
   year = {2019},
   address = {Long Beach, California, USA},
   note = {Best CVsports paper award},
   doi = {10.1109/CVPRW.2019.00306},
   keywords = {Soccer, Semantic segmentation, Artificial intelligence, Machine learning, Deep learning, CNN, DeepSport, Best paper award},
   url = {http://hdl.handle.net/2268/234413},
   pdf = {https://orbi.uliege.be/bitstream/2268/234413/1/Cioppa2019ARTHuS.pdf} 
   }
   




2. Adrien Deliège, Anthony Cioppa, and Marc Van Droogenbroeck. An Effective Hit-or-Miss Layer Favoring Feature Interpretation as Learned Prototypes Deformations. In AAAI Conference on Artificial Intelligence, Workshop on Network Interpretability for Deep Learning, Honolulu, Hawaii, USA, pages 1-8, January 2019. Keyword(s): Deep learning, Machine learning, Artificial intelligence, Neural network, Classification, Capsule, HitNet, Hit-or-miss layer, Feature interpretation, Centripetal loss, Prototype, DeepSport.
   

   @inproceedings{Deliege2019AnEffective,
   title = {An Effective Hit-or-Miss Layer Favoring Feature Interpretation as Learned Prototypes Deformations},
   author = {Deli\`ege, Adrien and Cioppa, Anthony and {Van Droogenbroeck}, Marc},
   booktitle = {AAAI Conference on Artificial Intelligence, Workshop on Network Interpretability for Deep Learning},
   pages = {1-8},
   year = {2019},
   month = {January},
   address = {Honolulu, Hawaii, USA},
   keywords = {Deep learning, Machine learning, Artificial intelligence, Neural network, Classification, Capsule, HitNet, Hit-or-miss layer, Feature interpretation, Centripetal loss, Prototype, DeepSport},
   url = {http://www.telecom.ulg.ac.be/publi/publications/deliege/Deliege2019AnEffective/},
   pdf = {https://orbi.uliege.be/bitstream/2268/229746/1/Deliege2019AnEffective.pdf} 
   }
   




3. Adrien Deliège, A. Kumar, Maxime Istasse, Christophe De Vlesschouwer, and Marc Van Droogenbroeck. Ordinal Pooling. In British Machine Vision Conference (BMVC), Cardiff, Wales, pages 1-12, September 2019. Keyword(s): Deep learning, Machine learning, Pooling, Artificial intelligence, Neural network, Convolutional layer, CNN, DeepSport.
   

   @inproceedings{Deliege2019OrdinalPooling,
   title = {Ordinal Pooling},
   author = {Deli\`ege, Adrien and A. Kumar and Istasse, Maxime and {De Vlesschouwer}, Christophe and {Van Droogenbroeck}, Marc},
   booktitle = {British Machine Vision Conference (BMVC)},
   pages = {1-12},
   year = {2019},
   month = {September},
   address = {Cardiff, Wales},
   keywords = {Deep learning, Machine learning, Pooling, Artificial intelligence, Neural network, Convolutional layer, CNN, DeepSport},
   url = {https://orbi.uliege.be/handle/2268/238475},
   pdf = {https://orbi.uliege.be/bitstream/2268/238475/1/Ordinal_Pooling.pdf} 
   }
   




4. Michaël Fonder and Marc Van Droogenbroeck. Mid-Air: A multi-modal dataset for extremely low altitude drone flights. In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), UAVision, Long Beach, California, USA, pages 553-562, June 2019. Keyword(s): UAV, Dataset, Mid-Air, Positioning, Benchmark, Drone, Artificial Intelligence, Deep learning.
   

   @inproceedings{Fonder2019MidAir,
   title = {{Mid-Air}: A multi-modal dataset for extremely low altitude drone flights},
   author = {Fonder, Micha\"el and {Van Droogenbroeck}, Marc},
   booktitle = {IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), UAVision},
   pages = {553-562},
   month = {June},
   year = {2019},
   address = {Long Beach, California, USA},
   keywords = {UAV, Dataset, Mid-Air, Positioning, Benchmark, Drone, Artificial Intelligence, Deep learning},
   doi = {10.1109/CVPRW.2019.00081},
   url = {https://ieeexplore.ieee.org/document/9025697},
   pdf = {https://orbi.uliege.be/bitstream/2268/234665/1/Fonder2019MidAir.pdf} 
   }
   




5. Philippe Latour and Marc Van Droogenbroeck. Dual Approaches for Elliptic Hough Transform: Eccentricity/Orientation vs Center based. In IAPR International Conference on Discrete Geometry for Computer Imagery (DGCI), Lecture Notes in Computer Science, pages 367-379, 2019. Keyword(s): Ellipse detection, Ellipse matching, Hough transform, Pencil of conics, Tangential equation.
   

   @inproceedings{Latour2018Dual,
   title = {Dual Approaches for Elliptic {H}ough Transform: Eccentricity/Orientation vs Center based},
   author = {Latour, Philippe and {Van Droogenbroeck}, Marc},
   booktitle = {IAPR International Conference on Discrete Geometry for Computer Imagery (DGCI)},
   series = {Lecture Notes in Computer Science},
   year = {2019},
   pages = {367-379},
   keywords = {Ellipse detection, Ellipse matching, Hough transform, Pencil of conics, Tangential equation},
   doi = {10.1007/978-3-030-14085-4_29},
   url = {http://hdl.handle.net/2268/231074} 
   }
   




6. Giovanny Moncayo-Unda, Ismaël Saadi, Marc Van Droogenbroeck, and Mario Cools. SmartGPS: An android app for collecting urban mobility data. In BIVEC/GIBET Transport Research Days, Ghent, Belgium, pages 1-10, May 2019. Keyword(s): Transport, GPS.
   

   @inproceedings{Moncayo2019SmartGPS,
   title = {Smart{GPS}: An android app for collecting urban mobility data},
   author = {Moncayo-Unda, Giovanny and Saadi, Isma\"el and Van Droogenbroeck, Marc and Cools, Mario},
   booktitle = {BIVEC/GIBET Transport Research Days},
   pages = {1-10},
   year = {2019},
   month = {May},
   address = {Ghent, Belgium},
   keywords = {Transport, GPS} 
   }
   

1. Marc Van Droogenbroeck, Philippe Latour, Jean-Marc Wagner, Vincent Pierlot, and Renaud Vandeghen. Principes des télécommunications analogiques et numériques: manuel des répétitions. Manuel avec les énoncés des répétitions, Université de Liège, 2019. Keyword(s): Telecommunications, Notes de cours, Lecture notes, Exercices, ELEN008.
   

   @booklet{Vandroogenbroeck-Principes-exercices,
   year = {2019},
   author = {Van Droogenbroeck, Marc and Latour, Philippe and Wagner, Jean-Marc and Pierlot, Vincent and Vandeghen, Renaud},
   title = {Principes des t\'el\'ecommunications analogiques et num\'eriques: manuel des r\'ep\'etitions},
   url = {http://hdl.handle.net/2268/233407},
   pdf = {https://orbi.uliege.be/bitstream/2268/233407/7/elen0008-repetitions.pdf},
   howpublished = {Manuel avec les \'enonc\'es des r\'ep\'etitions, Universit\'e de Li\`ege},
   keywords = {Telecommunications, Notes de cours, Lecture notes, Exercices, ELEN008} 
   }
   




2. Marc Van Droogenbroeck, Jean-Marc Wagner, Vincent Pierlot, and Philippe Latour. Analysis and Design of Telecommunications Systems: Manual of Exercises. Manuel avec les énoncés des répétitions, Université de Liège, 2019. Keyword(s): Telecommunications, Exercices, Lecture notes, ELEN017.
   

   @booklet{Vandroogenbroeck-Analysis-Manual,
   year = {2019},
   author = {Van Droogenbroeck, Marc and Wagner, Jean-Marc and Pierlot, Vincent and Latour, Philippe},
   title = {Analysis and Design of Telecommunications Systems: Manual of Exercises},
   url = {http://hdl.handle.net/2268/239453},
   pdf = {https://orbi.uliege.be/bitstream/2268/239453/1/elen017-exercises.pdf},
   howpublished = {Manuel avec les \'enonc\'es des r\'ep\'etitions, Universit\'e de Li\`ege},
   keywords = {Telecommunications, Exercices, Lecture notes, ELEN017} 
   }
   

1. Marc Van Droogenbroeck, Marc Braham, and Sébastien Piérard. Foreground and background detection method. Chinese Patent Office, CN109389618A, February 2019. Keyword(s): Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence.
   

   @misc{Vandroogenbroeck2019Foreground-CN,
   title = {Foreground and background detection method},
   author = {{Van Droogenbroeck}, Marc and Braham, Marc and Pi{\'e}rard, S{\'e}bastien},
   month = {February},
   year = {2019},
   howpublished = {Chinese Patent Office, CN109389618A},
   keywords = {Background subtraction, Semantic segmentation, Patent, Machine learning, Deep learning, Artificial intelligence},
   url = {http://hdl.handle.net/2268/235851} 
   }
   




2. Marc Van Droogenbroeck, Adrien Deliège, and Anthony Cioppa. Image classification using neural networks. World Intellectual Property Organization, WO 2019/238976, 55 pages, December 2019. Keyword(s): Patent, Machine learning, Deep learning, Artificial intelligence, HitNet, Capsule, Data augmentation, DeepSport.
   

   @misc{Vandroogenbroeck2019Image,
   title = {Image classification using neural networks},
   author = {{Van Droogenbroeck}, Marc and Deli\`ege, Adrien and Cioppa, Anthony},
   month = {December},
   year = {2019},
   howpublished = {World Intellectual Property Organization, WO 2019/238976, 55 pages},
   keywords = {Patent, Machine learning, Deep learning, Artificial intelligence, HitNet, Capsule, Data augmentation, DeepSport},
   url = {https://orbi.uliege.be/handle/2268/226179} 
   }
   

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