PhD thesis

• W. Caarls, Automated Design of Application-Specific Smart Camera Architectures, Delft University of Technology, 2008, 1-184

Journal papers

• E. L. Luz and W. Caarls, Comparison of reinforcement learning techniques for controlling a CSTR process, in: Brazilian Journal of Chemical Engineering, 2023, DOI 10.1007/s43153-023-00422-y.
• G. Lins Tenorio and W. Caarls, Automatic visual estimation of tomato cluster maturity in plant rows, in: Machine Vision and Applications, Vol. 32, No. 4, July 2021, DOI 10.1007/s00138-021-01202-9.
• L. Santiago, V. Leticia, F. Rangel, F. Firmino, D.S. Menasche, W. Caarls, M. Breternitz, S. Kundu, P.M.V. Lima, and F.M.G. Franca, Weightless Neural Networks as Memory Segmented Bloom Filters, in: Neurocomputing, Vol. 416, November 2020, DOI 10.1016/j.neucom.2020.01.115.
• B. Calli, W. Caarls, M. Wisse, and P.P. Jonker, Viewpoint optimization for aiding grasp synthesis algorithms using reinforcement learning, in: Advanced Robotics, Vol. 32, No. 20, September 2018, DOI 10.1080/01691864.2018.1520145.
• B. Calli, W. Caarls, M. Wisse, and P.P. Jonker, Active Vision via Extremum Seeking for Robots in Unstructured Environments: Applications in Object Recognition and Manipulation, in: IEEE Transactions on Automation Science and Engineering, Vol. 15, No. 4, March 2018, DOI 10.1109/TASE.2018.2807787.
• I. Koryakovskiy, M. Kudruss, H. Vallery, R. Babuska, and W. Caarls, Model-Plant Mismatch Compensation Using Reinforcement Learning, in: IEEE Robotics and Automation Letters, Vol. 3, No. 3, January 2018, DOI 10.1109/LRA.2018.2800106.
• I. Koryakovskiy, M. Kudruss, R. Babuska, W. Caarls, C. Kirches, K. Mombaur, J.P. Schloder, and H. Vallery, Benchmarking model-free and model-based optimal control for bipedal locomotion, in Robotics and Autonomous Systems, Vol. 92, No. C, June 2017, pp. 81-90, DOI 10.1016/j.robot.2017.02.006.
• A. Reiffers-Masson, E. Hargreaves, E. Altman, W. Caarls, D. S. Menasche, Timelines are Publisher-Driven Caches: Analyzing and Shaping Timeline Networks, in ACM SIGMETRICS Performance Evaluation Review, Vol. 44, No. 3, December 2016, pp. 26-29, DOI 10.1145/3040230.3040237.
• B. Palma, C. Lima, W. Caarls, and D. Vettorazzi, Which Probabilistic Roadmap method should be used by a robot in an actual environment? An analysis of the main methods through simulations, in IEEE Latin America Transactions, Vol. 14, No. 4, April 2016, pp. 2020-2025, DOI 10.1109/TLA.2016.7483549.
• W. Caarls and E. Schuitema, Parallel On-Line Temporal Difference Learning for Motor Control, in IEEE Transactions on Neural Networks and Learning Systems, Vol. 27, No. 7, July 2016, pp. 1457-1468, DOI 10.1109/TNNLS.2015.2442233.
• W.J. Wolfslag, M.C. Plooij, W. Caarls, S. van Weperen, and G.A.D. Lopes, Dissipatively actuated manipulation, in Control Engineering Practice, Vol. 34, No. 1, January 2015, pp. 68-76, DOI 10.1016/j.conengprac.2014.09.003.
• O. Akman, R. Poelman, W. Caarls, and P. Jonker, Multi-cue hand detection and tracking for a head-mounted augmented reality system, in: Machine Vision and Applications, Vol. 24, No. 1, July 2013, pp. 931-946, DOI 10.1007/s00138-013-0500-6.
• W. Caarls, B. Rieger, A.H.B. de Vries, D.J. Arndt-Jovin, and T.M. Jovin, Minimizing Light Exposure with the Programmable Array Microscope, in: Journal of Microscopy, Vol. 241, No. 1, January 2011, pp. 101-110, DOI 10.1111/j.1365-2818.2010.03413.x.
• S. Kantelhardt, W. Caarls, A.H.B. de Vries, G.M. Hagen, T.M. Jovin, W. Schulz-Schaeffer, V. Rohde, A. Giese, and D.J. Arndt-Jovin, Specific Visualization of Glioma Cells in Living Low-grade Tumor Tissue, in: PLoS ONE, Vol. 5, No. 6, June 2010, pp. e11323, DOI 10.1371/journal.pone.0011323.
• W. Caarls, M.S. Celej, A.P. Demchenko, and T.M. Jovin, Characterization of coupled ground state and excited state equilibria by fluorescence spectral deconvolution, in: Journal of Fluorescence, Vol. 20, No. 1, January 2010, pp. 181-190, DOI 10.1007/s10895-009-0536-1 (Matlab code).
• M.S. Celej, W. Caarls, A.P. Demchenko, and T.M. Jovin, A triple emission fluorescent probe reveals distinctive amyloid fibrillar polymorphism of wild-type alpha-synuclein and its familial Parkinsons disease mutants, in: Biochemistry, Vol. 48, No. 31, July 2009, pp. 7465-7472, DOI 10.1021/bi9003843.
• G. Hagen, W. Caarls, K. Lidke, A. de Vries, C. Fritsch, B. Barisas, D. Arndt-Jovin, and T. Jovin, Fluorescence recovery after photobleaching and photoconversion in multiple arbitrary regions of interest using a programmable array microscope, in: Microscopy Research and Technique, Vol. 72, No. 6, June 2009, pp. 431-440, DOI 10.1002/jemt.20686.
• D.J. Arndt-Jovin, S.R. Kantelhardt, W. Caarls, A.H.B. de Vries, A. Giese, and T.M. Jovin, Tumor-Targeted Quantum Dots Can Help Surgeons Find Tumor Boundaries, in: IEEE Transactions on Nanobioscience, Vol. 8, No. 1, March 2009, pp. 65-71, DOI 10.1109/TNB.2009.2016548.
• W. Caarls, P.P. Jonker, and H. Corporaal, Skeletons and Asynchronous RPC for Embedded Data- and Task Parallel Image Processing, in: IEICE Transactions on Information and Systems, Vol. E89-D, No. 7, July 2006, pp. 2036-2043, DOI 10.1093/ietisy/e89-d.7.2036. This is an extended version of the MVA 2005 paper of the same name.

Peer-reviewed conference papers

• F.F. Martins, T.M. Carvalho, A. Celecia, A.I.S. Oliveira, G.B.P. Barbosa, M.B.R. Vellasco, W. Caarls, K. Figueiredo, and A.C. Leite, Sistema de navegação autônoma para o robô agrícola Soybot, in: 14o Simpósio Brasileiro de Automação Inteligente (Online, October 17-20), Online, 2021.
• R.G. Oliveira and W. Caarls, A History-based Framework for Online Continuous Action Ensembles in Deep Reinforcement Learning, in: Proc. 13th International Conference on Agents and Artificial Intelligence (ICAART) (Online, February 4-6), Online, 2021. DOI 10.5220/0010199005800588.
• E. Batista, W. Caarls, L.A. Forero, and M.A. Pacheco, Training an Agent to Find and Reach an Object in Different Environments using Visual Reinforcement Learning and Transfer Learning, in: Proc. 13th International Conference on Agents and Artificial Intelligence (ICAART) (Online, February 4-6), Online, 2021. DOI 10.5220/0010236807320741.
• R.G. Oliveria and W. Caarls, Comparing Action Aggregation Strategies in Deep Reinforcement Learning with Continuous Action, in: Anais do Congresso Brasileiro de Automática 2020 (Online, November 23-26), Online, 2020. DOI 10.48011/asba.v2i1.1547.
• W. Caarls, Deep Reinforcement Learning with embedded LQR Controllers, in: Proc. 21st IFAC World Congress (Berlin, July 11-17), Germany, 2020. DOI 10.1016/j.ifacol.2020.12.2261.
• T.M. Carvalho, G.L. Tenorio, K. Figueiredo, M.B.R. Vellasco, and W. Caarls, Comparison of Machine Learning Models for Total Dengue Cases Prediction, in: Proc. XVI Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2019) (Salvador, October 15-18), Brazil, 2019.
• G.L. Tenorio, F.F. Martins, T.M. Carvalho, A.C. Leite, K. Figueiredo, M.B.R. Vellasco, and W. Caarls, Comparative Study of Computer Vision Models for Insect Pest Identification in Complex Backgrounds, in: Proc. 12th International Conference on Developments in eSystems Engineering (DeSE 2019) (Kazan, October 7-10), Russia, 2019. DOI 10.1109/DeSE.2019.00106.
• W. Barbosa, A.I.S. Oliveira, G.B.P. Barbosa, A.C. Leite, K. Figueiredo, M.B.R. Vellasco, and W. Caarls, Design and Development of an Autonomous Mobile Robot for Inspection of Soy and Cotton Crops, in: Proc. 12th International Conference on Developments in eSystems Engineering (DeSE 2019) (Kazan, October 7-10), Russia, 2019. DOI 10.1109/DeSE.2019.00107.
• A.I.S. Oliveira, T.M. Carvalho, F.F. Martins, A.C. Leite, K. Figueiredo, M.B.R. Vellasco, and W. Caarls, On the Intelligent Control Design of an Agricultural Mobile Robot for Cotton Crop Monitoring, in: Proc. 12th International Conference on Developments in eSystems Engineering (DeSE 2019) (Kazan, October 7-10), Russia, 2019. DOI 10.1109/DeSE.2019.00108.
• L.S. de Araujo, L.D. Verona, F.M. Rangel, F.F. de Faria, D.S. Menasche, W. Caarls, M. Breternitz, S. Kundu, P.M.V. Lima, and F.M.G. Franca, Memory Efficient Weightless Neural Network using Bloom Filter, in: Proc. European Symposium on Artificial Neural Networks (ESANN) (Bruges, April 24-26), Belgium, 2019.
• G. Tenorio, C. Villalobos, L. Mendoza, E.C. da Silva, and Wouter Caarls, Improving Transfer Learning Performance: An Application in the Classification of Remote Sensing Data, in: Proc. 11th International Conference on Agents and Artificial Intelligence (ICAART) (Prague, Feb 19-21), Czech Republic, 2019.
• M. F. S. da Neto, G. S. Eduardo, E. C. da Silva, and W. Caarls, Computer vision based solutions for mav target detection and flight control, in: 10th international micro air vehicle competition and conference (IMAV) (Melbourne, Nov 17-23), Australia, 2018.
• F.C. Fernandez, and W. Caarls, Parameters tuning and optimization for Reinforcement Learning algorithms using Evolutionary Computing, in: Proc. International Conference on Information Systems and Computer Science (INCOSCOS) (Quito, Nov 14-18), Equador, 2018.
• S.A. Alves, W. Caarls, and P.M.V. Lima, Weightless Neural Network for High Frequency Trading, in: Proc. 2018 International Joint Conference on Neural Networks (IJCNN) (Rio de Janeiro, July 8-13), Brazil, 2018.
• I. Koryakovskiy, H. Vallery, R. Babuska, and W. Caarls, Evaluation of Physical Damage Associated with Action Selection Strategies in Reinforcement Learning, in: Proc. World Congress of the International Federation of Automatic Control (IFAC) (Toulouse, July 9-14), France, 2017.
• W. Caarls, E. Hargreaves, and D.S. Menasche, Q-caching: An Integrated Reinforcement-Learning Approach for Caching and Routing in Information-Centric Networks, in: Proc. 16th Brazilian Symposium on Computer Networks and Distributed Systems (Salvador, May 30-June 3), Brazil, 2016.
• B. Costa, W. Caarls, and D. S. Menasche, Dyna-MLAC: Trading Computational and Sample Complexities in Actor-Critic Reinforcement Learning, in: Proc. Brazilian Conference on Intelligent Systems (Natal, Nov 4-7), Brazil, 2015.
• K.N. McGuire, M. Tsukada, M. Toda, B.A.J. Lenseigne, W. Caarls, and P. Jonker, Novel Method for Simultaneous Acquisition of Visible and Near-Infrared Light using a Coded Infrared-Cut Filter, in: Proc. International Conference on Computer Analysis of Images and Patterns (Valetta, Sept 2-4), Malta, 2015.
• M. Bharatheesha, W. Caarls, W. Wolfslag, and M.Wisse, Distance Metric Approximation for State-Space RRTs Using Supervised Learning, in: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (Chicago, Sept 14-18), IL, USA, 2014.
• H. Meijdam, M.C. Plooij, and W. Caarls, Learning while preventing mechanical failure due to random motions, in: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (Tokyo Big Sight, November 3-7), Japan, 2013 (slides).
• J. Pen, W. Caarls. M. Wisse, and R. Babuska, Evolutionary Co-Optimization of Control and System Parameters for a Resonating Robot Arm, in: Proc. IEEE International Conference on Robotics and Automation (Karlsruhe, May 6-10), Karlsruhe Institute of Technology, Germany, 2013
• B. Calli, W. Caarls, P.P. Jonker and M. Wisse, Comparison of Extremum Seeking Control Algorithms for Robotic Applications, in: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (Vilamoura, October 7-12), University of Coimbra, Portugal, 2012
• B. van Vliet, W. Caarls, E. Schuitema and P.P. Jonker, Accelerating reinforcement learning on a robot by using subgoals in a hierarchical framework, in: Proc. 23rd Benelux Conference on Artificial Intelligence (Ghent, November 3-4), KAHO St. Lieven, Ghent, 2011 (poster)
• E. Schuitema, W. Caarls, M. Wisse, P.P. Jonker and R. Babuska, The Effects of Large Disturbances on On-Line Reinforcement Learning for a Walking Robot, in: Proc. 22nd Benelux Conference on Artificial Intelligence (Luxembourg, October 25-26), University of Luxembourg, Luxembourg, 2010
• W. Caarls, P.P. Jonker, and H. Corporaal, Algorithmic Skeletons for Stream Programming in Embedded Heterogeneous Parallel Image Processing, in: Proc. 20th IEEE International Parallel & Distributed Processing Symposium (Rhodes Island, April 25-29), IEEE Computer Society Technical Committee on Parallel Processing, Greece, 2006, 1-9 (ppt)
• F. Mantz, P.P. Jonker, and W. Caarls, Behavior-Based Vision on a 4 Legged Soccer Robot, in: RoboCup 2005 (Lecture Notes in Computer Science 4020), 2005, 480-487
• H. Broers, W. Caarls, P.P. Jonker, and R. Kleihorst, Architecture Study for Smart Cameras, in: Proc. EOS Conference on Industrial Imaging and Machine Vision (Munich, Germany, June 13-15), European Optical Society, 2005, 39-49
• W. Caarls, P.P. Jonker, and H. Corporaal, Skeletons and Asynchronous RPC for Embedded Data- and Task Parallel Image Processing, in: Proc. 9th IAPR Conference on Machine Vision Applications (Tsukuba Science City, May 16-18), MVA Conference Committee, Tokyo, 2005, 384-387 (ppt)
• W. Caarls, P.P. Jonker, and H. Corporaal, Benchmarks for SmartCam Development, in: Proceedings of Acivs 2003 (Advanced Concepts for Intelligent Vision Systems) (Ghent, Sept. 2-5), Ghent University, Ghent, 2003, 81-86 (poster)
• P.P. Jonker and W. Caarls, Application Driven Design of Embedded Real-Time Image Processors, in: Proceedings of Acivs 2003 (Advanced Concepts for Intelligent Vision Systems) (Ghent, Sept. 2-5), Ghent University, Ghent, 2003, 1-8

Conference abstracts

• P. A. A. De Beule, A. H. B. de Vries, W. Caarls, D. J. Arndt-Jovin and T. M. Jovin, A Generation-3 Programmable Array Microscope with Digital Micro-Mirror Device, in: Biophysical Journal, Vol. 98, No. 3, Supp. 1, January 2010, p. 178a.
• W. Caarls, M.S. Celej, A.P. Demchenko, and T.M. Jovin, Multiwavelength ratiometric fluorescence sensing, in: Proc. Methods and Applications of Fluorescence 2009, Budapest, Hungary, 6-9 September 2009, 184 (poster)
• W. Caarls, A.H.B. de Vries, D.J. Arndt-Jovin and T.M. Jovin, Arbitrary and Dynamic Patterning in a Programmable Array Microscope, in: Proc. Focus on Microscopy 2009, Krakow, Poland, 28-31 March 2009, 137 (ppt, NANODOTS 2009 poster)
• G.M. Hagen, W. Caarls, K.A. Lidke, A.H.B. de Vries, C. Fritsch, B.G. Barisas, D.J. Arndt-Jovin and T.M. Jovin, FRAP and Photoconversion in Multiple Arbitrary Regions of Interest Using a Programmable Array Microscope (PAM), in: Biophysical Journal, Vol. 96, No. 3, Supp. 1, February 2009, p. 281a.
• M.G. Botelho, W. Caarls, S. Kantelhardt, A. Cambi, G. Hagen, D. J. Arndt-Jovin and T. M. Jovin, A symbiosis: tracking cell signaling with expression probes, quantum dots and a programmable array microscope (PAM), in: Proc. EMC 2008 14th European Microscopy Congress, Volume 3: Life Science, Aachen, Germany, 1-5 September 2008, 335-336
• T.M. Jovin, G. Hagen, W. Caarls and D. J. Arndt-Jovin, Live cell microscopy of growth-factor dependent signal transduction pathways with a Programmable Array Microscope (PAM), in: Cytometry Part A 71A 745-746 (2007)
• D.J. Arndt-Jovin, G. Hagen, W. Caarls, A. Hil and T. M. Jovin, Biological applications of an LCoS-based programmable array microscope (PAM), in: Cytometry Part A 71A 512-512 (2007)
• G.M. Hagen, W. Caarls, M. Thomas, A. Hill, K.A. Lidke, B. Rieger, C. Fritsch, B. van Geest, T.M. Jovin and D.J. Arndt-Jovin, Biological applications of an LCoS-based PROGRAMMABLE ARRAY MICROSCOPE (PAM), in: Imaging, Manipulation and Analysis of Biomolecules, Cells, and Tissues V (Proc. Photonic West 2007, BiOS), San Jose, CA, USA, Jan.20-25, Proc. SPIE, vol. 6441, 2007, 26/S5
• W. Caarls, P.P. Jonker, and H. Corporaal, Data- and Task Parallel Image Processing on a Mixed SIMD-ILP Platform using Skeletons and Asynchronous RPC, in: M. Schweizer (eds.), Proc. 5th PROGRESS Workshop on Embedded Systems (Nieuwegein, Oct.20), STW, Utrecht, 2004, 27-34 (poster)
• W. Caarls, P.P. Jonker, and H. Corporaal, SmartCam Design Framework, in: M. Schweizer (eds.), Proc. 4th PROGRESS Workshop on Embedded Systems (Nieuwegein, Oct.22), STW, Utrecht, 2003, 1-8 (CD-ROM) (poster)
• W. Caarls, P.P. Jonker, and H. Corporaal, SmartCam: Devices for Embedded Intelligent Cameras, in: M. Schweizer (eds.), Proc. 3rd PROGRESS Workshop on Embedded Systems (Utrecht, Oct.24), STW, Utrecht, 2002, 1-4 (CD-ROM).

Book chapters

• G.M. Hagen, K. A. Lidke, B. Rieger, W. Caarls, D. J. Arndt-Jovin and T. M. Jovin, Dynamics of membrane receptors: single molecule tracking of quantum dot liganded epidermal growth factor, in: Single molecule dynamics in life sciences, Wiley, Orlando, 2008, pp. 117-130

Patents

• T. Jovin, W. Caarls, and A. de Vries, OPTICAL MODULATOR DEVICE AND SPATIO-TEMPORALLY LIGHT MODULATED IMAGING SYSTEM, WO/2011/116904, September 2011, pp. 1-39
• R.P. Kleihorst, A.J. Bink, H. Broers, W. Caarls, and S.H. Fatemi, IMAGE PROCESSING APPARATUS AND METHOD, WO/2005/106786, November 2005, pp. 1-21

Invited talks

• W. Caarls, Reinforcement learning tutorial, Koroibot Summer School, University of Heidelberg, Heidelberg, Germany, September 22-26, 2014.
• W. Caarls, Parallel DYNA, 8th Barbados Workshop on Reinforcement Learning, Bellairs Research Institute, Holetown, Barbados, May 2, 2013.
• W. Caarls, Parallel Real-Time Reinforcement Learning, 6th Barbados Workshop on Reinforcement Learning, Bellairs Research Institute, Holetown, Barbados, March 18, 2011.
• W. Caarls, GPU Programming Paradigms, General Purpose GPU Symposium, Eindhoven University of Technology, Eindhoven, The Netherlands, September 1st, 2010.
• W. Caarls, Design Space Exploration, EVA project meeting, Eindhoven University of Technology, Eindhoven, The Netherlands, September 4th, 2009.
• W. Caarls, Pseudo-dynamic C metaprogramming, 7th Stratego User Days, Delft University of Technology, Delft, The Netherlands, November 30th, 2006.
• W. Caarls, Parallel Image Processing, IST-PhD lunch seminar, Delft University of Technology, Delft, The Netherlands, October 26th, 2006.