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List of results

Smart App for PD + (Pérez-López, Carlos, et al. "Monitoring Mo … Pérez-López, Carlos, et al. "Monitoring Motor Fluctuations in Parkinson’s Disease Using a Waist-Worn Inertial Sensor." Advances in Computational Intelligence. Springer International Publishing, 2015. 461-474.LeMoyne, Robert, and Timothy Mastroianni. "Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor." Mobile Health Technologies: Methods and Protocols (2015): 335-358.es: Methods and Protocols (2015): 335-358.)
Simulating cyber attacks and countermeasures using Cyber Operations Research Gym (CybORG) + (Quantitative Resilience Modeling for Auton … Quantitative Resilience Modeling for Autonomous Cyber Defense https://rlj.cs.umass.edu/2025/papers/RLJ_RLC_2025_99.pdf Interpreting Agent Behaviors in Reinforcement-Learning-Based Cyber-Battle Simulation Platformshttps://arxiv.org/html/2506.08192v1CybORG:https://github.com/cage-challenge/cyborg?utm_source=chatgpt.comge-challenge/cyborg?utm_source=chatgpt.com)
Cross-Spectrum Ocular Identity Recognition via Deep Learning + (R. Jillela and A. Ross, "Matching face aga … R. Jillela and A. Ross, "Matching face against iris images using periocular information," 2014 IEEE International Conference on Image Processing (ICIP), Paris, 2014, pp. 4997-5001.doi: 10.1109/ICIP.2014.7026012: https://ieeexplore.ieee.org/document/7026012P. R. Nalla and A. Kumar, "Toward More Accurate Iris Recognition Using Cross-Spectral Matching," in IEEE Transactions on Image Processing, vol. 26, no. 1, pp. 208-221, Jan. 2017.doi: 10.1109/TIP.2016.2616281: https://ieeexplore.ieee.org/document/7587438tps://ieeexplore.ieee.org/document/7587438)
Constrained dynamic path planning for truck and trailer + (R. Siegwart and I. R. Nourbakhsh,Introduct … R. Siegwart and I. R. Nourbakhsh,Introduction to Autonomous Mobile Robots. Scituate, MA, USA: Bradford Company, 2004A. Nozad, Heavy vehicle path stability control for collision avoidance applications," Master's thesis, Chalmers university of technology, 2011J. G. Fernandez, A vehicle dynamics model for driving simulators," Master's thesis, Chalmers university of technology, 2012s, Chalmers university of technology, 2012)
Identification and Classification of Automotive Radar Interference using Data-driven Methods + (Radar interference: https://www.analog.com … Radar interference: https://www.analog.com/en/resources/analog-dialogue/articles/automotive-radar-sensors-and-congested-radio-spectrum-an-urban-electronic-warfare.htmlEquipment: https://www.ti.com/tool/AWR2944EVM, and https://www.ti.com/tool/DCA1000EVM,M, and https://www.ti.com/tool/DCA1000EVM,)
Explainable GNNs for Security Verification of RISC-V Cores + (Reimann, Lennart M., et al. ”Qtflow: Quant … Reimann, Lennart M., et al. ”Qtflow: Quantitative timing-sensitive information flow for security-aware hardware design on rtl.” 2024 International VLSI Symposium on Technology, Systems and Applications (VLSI TSA). IEEE, 2024.Gosch, Lukas, et al. ”Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks.” Transactions on Machine Learning Research.Transactions on Machine Learning Research.)
Semantic Analysis of 2D Maps With a Metric-Topological Approach + (Rottmann, Axel, et al. "Semantic place cla … Rottmann, Axel, et al. "Semantic place classification of indoor environments with mobile robots using boosting." AAAI. Vol. 5. 2005.Liu, Ziyuan, and Georg von Wichert. "Extracting semantic indoor maps from occupancy grids." Robotics and Autonomous Systems (2013).Schroter, Derik, Michael Beetz, and J-S. Gutmann. "Rg mapping: Learning compact and structured 2d line maps of indoor environments." Robot and Human Interactive Communication, 2002. Proceedings. 11th IEEE International Workshop on. IEEE, 2002.EEE International Workshop on. IEEE, 2002.)
Time series anomaly detection for heavy-duty vehicles + (Ruiz, C., Menasalvas, E., & Spiliopoul … Ruiz, C., Menasalvas, E., & Spiliopoulou, M. (2009). C-denstream: Using domain knowledge on a data stream. In Discovery Science: 12th International Conference, DS 2009, Porto, Portugal, October 3-5, 2009 12 (pp. 287-301). Springer Berlin Heidelberg.Cao, F., Estert, M., Qian, W., & Zhou, A. (2006, April). Density-based clustering over an evolving data stream with noise. In Proceedings of the 2006 SIAM international conference on data mining (pp. 328-339). Society for industrial and applied mathematics.Fan, Y., Nowaczyk, S., & Antonelo, E. A. (2016). Predicting air compressor failures with echo state networks. In PHM Society European Conference (Vol. 3, No. 1).Fan, Y., Nowaczyk, S., & Rögnvaldsson, T. (2020). Transfer learning for remaining useful life prediction based on consensus self-organizing models. Reliability Engineering & System Safety, 203, 107098.Ahmad, S., Lavin, A., Purdy, S., & Agha, Z. (2017). Unsupervised real-time anomaly detection for streaming data. Neurocomputing, 262, 134-147.Lavin, A., & Ahmad, S. (2015, December). Evaluating real-time anomaly detection algorithms--the Numenta anomaly benchmark. In 2015 IEEE 14th international conference on machine learning and applications (ICMLA) (pp. 38-44). IEEE.Wu, K., Zhang, K., Fan, W., Edwards, A., & Philip, S. Y. (2014, December). Rs-forest: A rapid density estimator for streaming anomaly detection. In 2014 IEEE international conference on data mining (pp. 600-609). IEEE.Hendrickx, K., Meert, W., Mollet, Y., Gyselinck, J., Cornelis, B., Gryllias, K., & Davis, J. (2020). A general anomaly detection framework for fleet-based condition monitoring of machines. Mechanical Systems and Signal Processing, 139, 106585.monitoring of machines. Mechanical Systems and Signal Processing, 139, 106585.)
Agent and object detection and classification in a warehouse setting + (SAS2-project, http://islab.hh.se/mediawiki … SAS2-project, http://islab.hh.se/mediawiki/SAS2ROS - Robot Operating System, http://www.ros.org/ OpenCv - http://opencv.org/Lalonde, Jean-Francois; Vandapel, Nicolas; Huber, Daniel; Hebert, Martial; Natural terrain classification using three-dimensional ladar data for ground robot mobility, Journal of Field Robotics, Vol. 23, No. 10, pp. 839 - 861, November, 2006Mosberger, Rafael; Vision-based human detection from mobile machinery in industrial environments, Thesis, Örebro University, Sweden, 2016Saarinen, Jari P.; Andreasson, Henrik; Stoyanov, Todor; Lilienthal, Achim J.; 3D normal distributions transform occupancy maps: An efficient representation for mapping in dynamic environments, The International Journal of Robotics Research, Vol 32, Issue 14, pp. 1627 – 1644, 2013h, Vol 32, Issue 14, pp. 1627 – 1644, 2013)
Adaptive warning field system + (SAS2-project, http://islab.hh.se/mediawiki … SAS2-project, http://islab.hh.se/mediawiki/SAS2ROS - Robot Operating System, http://www.ros.org/OpenCv - http://opencv.org/ Nemati, Hassan, Åstrand, Björn (2014). Tracking of People in Paper Mill Warehouse Using Laser Range Sensor. 2014 UKSim-AMSS 8th European Modelling Symposium, EMS 2014, Pisa, Italy, 21-23 October, 2014.Power, P. Wayne, and Johann A. Schoonees. "Understanding background mixture models for foreground segmentation." Proceedings image and vision computing New Zealand. Vol. 2002. 2002.on computing New Zealand. Vol. 2002. 2002.)
Model behaviour of agents in a warehouse setting + (SAS2-project, http://islab.hh.se/mediawiki … SAS2-project, http://islab.hh.se/mediawiki/SAS2ROS - Robot Operating System, http://www.ros.org/OpenCv - http://opencv.org/Lidström, Kristoffer; Situation-Aware vehicles – supporting the next generation of cooperative traffic system, PhD thesis, Örebro university, 2012.Lundström, Jens; Järpe, Eric; Verikas, Antanas; Detecting and exploring deviating behaviour of smart home residents, Expert systems with applications., 55, s. 429-440, 2016Lidström, Kristoffer; Larsson, Tony; Act normal: using uncertainty about driver intentions as a warning criterion, 16th World Congress on Intelligent Transportation Systems (ITS WC), 21-25 September, 2009, Stockholm, SwedenLidström, Kristoffer; Model-based Estimation of Driver Intentions Using Particle Filtering, Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems Beijing, China, October 12-15, 2008ystems Beijing, China, October 12-15, 2008)
Graph Neural Networks for Traffic Flow Forecasting + (Scarselli, F., Gori, M., Tsoi, A. C., Hagenbuchner, M., & Monfardini, G. (2008). The graph neural network model. IEEE transactions on neural networks, 20(1), 61-80.)
Graph Neural Networks for cardiovascular disease + (Scarselli, F., Gori, M., Tsoi, A. C., Hagenbuchner, M., & Monfardini, G. (2008). The graph neural network model. IEEE transactions on neural networks, 20(1), 61-80.)
Supervised/Unsupervised Electricity Customer Classification + (Schneider, Kevin P., et al. "Evaluation of conservation voltage reduction (CVR) on a national level." Pacific Northwest National Laboratory report (2010).)
Uncertainty quantification for data driven clinical decision making + (Sensoy, Murat, Lance Kaplan, and Melih Kandemir. "Evidential deep learning to quantify classification uncertainty." arXiv preprint arXiv:1806.01768 (2018). Amini, Alexander, et al. "Deep evidential regression." arXiv preprint arXiv:1910.02600 (2019).)
Representation of Complex Data Types for Machine Learning + (Statistical Relational Learning Knowledge Representation)
Detecting changes in causal relations + (Structural causal discovery techniques: https://arxiv.org/pdf/1211.3295.pdf Change detection in Granger causality: http://cowles.yale.edu/sites/default/files/files/pub/d20/d2059.pdf)
Automatic Generation of Realtime Machine Learning Architectures + (Subbaraj, H., 2020. Using Dataflow for Machine Learning Inference. Anderson, J., Alkabani, Y. and El-Ghazawi, T., 2019. Towards Energy-Quality Scaling in Deep Neural Networks. IEEE Design & Test.)
Smart sensor + (Surya G. Nurzaman, Utku Culha, Luzius Brod … Surya G. Nurzaman, Utku Culha, Luzius Brodbeck, Liyu Wang, Fumiya Iida. (2013) Active Sensing System with In Situ Adjustable Sensor Morphology. PLoS ONE 8(12):e84090. doi:10.1371/journal.pone.0084090Robin R. Murphy. Dempster–Shafer Theory for Sensor Fusion in Autonomous Mobile Robots. IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, VOL. 14, NO. 2, APRIL 1998 197.UTOMATION, VOL. 14, NO. 2, APRIL 1998 197.)
Investigating Robustness of DNNs + (Szegedy, Christian, et al. "Intriguing pro … Szegedy, Christian, et al. "Intriguing properties of neural networks." arXiv preprint arXiv:1312.6199 (2013).Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. "Reducing the dimensionality of data with neural networks." Science 313.5786 (2006): 504-507.Hinton, Geoffrey E. "Learning multiple layers of representation." Trends in cognitive sciences 11.10 (2007): 428-434.Nguyen, Anh, Jason Yosinski, and Jeff Clune. "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images." arXiv preprint arXiv:1412.1897 (2014).Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012.ural information processing systems. 2012.)
Real-time bladder scanner + (TBD)
Smart Home Simulation + (Teresa Garcia-Valverde, Francisco Campuzan … Teresa Garcia-Valverde, Francisco Campuzano, Emilio Serrano, Ana Villa, and Juan A. Botia. 2012. Simulation of human behaviours for the validation of Ambient Intelligence services: A methodological approach. J. Ambient Intell. Smart Environ. 4, 3 (August 2012), 163-181. Juan A. Botia, Ana Villa, Jose Palma, Ambient Assisted Living system for in-home monitoring of healthy independent elders, Expert Systems with Applications, Volume 39, Issue 9, July 2012, Pages 8136-8148.Pavel, M.; Jimison, H.B.; Wactlar, H.D.; Hayes, T.L.; Barkis, W.; Skapik, J.; Kaye, J., "The Role of Technology and Engineering Models in Transforming Healthcare," Biomedical Engineering, IEEE Reviews in , vol.6, no., pp.156,177, 2013.Reviews in , vol.6, no., pp.156,177, 2013.)
Automatic Machine Learning (AUTO-AUTO-ENCODER!) + (The following paper summarises the algorit … The following paper summarises the algorithm configuration in the different domain :http://aad.informatik.uni-freiburg.de/papers/16-AUTOML-AutoNet.pdfThis paper presents the initial idea behind Bayesian optimization for estimating parameter:https://www.cs.ubc.ca/~hutter/papers/10-TR-SMAC.pdfPrevious master thesis on applying autoencoder for histogram data:Robin Ng, “Efficient Implementation of Histogram Dimension Reduction using Deep Learning”, 2017.sion Reduction using Deep Learning”, 2017.)
Vehicle Operation Classification + (Time series classification Unsupervised and semi-supervised clustering ...)
Autonomous Trust and Access Control in Coalition IoBT Networks + (Trust-based Blockchain Authorization for I … Trust-based Blockchain Authorization for IoThttps://arxiv.org/pdf/2104.00832 Blockchain-based Decentralized Trust Management in IoT: Systems, Requirements and Challengeshttps://link.springer.com/article/10.1007/s40747-023-01058-8UAVouchhttps://ieeexplore.ieee.org/document/9448085tps://ieeexplore.ieee.org/document/9448085)

Digital Twin - AFRY + (Victor Svahn)

Body posture alignment feedback using xAI + (Vivek Anand Thoutam, Anugrah Srivastava, T … Vivek Anand Thoutam, Anugrah Srivastava, Tapas Badal, Vipul Kumar Mishra, G. R. Sinha, Aditi Sakalle, Harshit Bhardwaj, Manish Raj, "Yoga Pose Estimation and Feedback Generation Using Deep Learning", Computational Intelligence and Neuroscience, vol. 2022, Article ID 4311350, 12 pages, 2022. https://doi.org/10.1155/2022/4311350Cooney, Martin & Pihl, J & Larsson, H & Orand, A & Aksoy, Eren. (2019). Exercising with an "Iron Man": Design for a Robot Exercise Coach for Persons with Dementia. 10.13140/RG.2.2.14286.61765. Chaudhari, Ajay, et al. "Yog-guru: Real-time yoga pose correction system using deep learning methods." 2021 International Conference on Communication information and Computing Technology (ICCICT). IEEE, 2021. https://doi.org/10.1109/ICCICT50803.2021.9509937EE, 2021. https://doi.org/10.1109/ICCICT50803.2021.9509937)
Profiling ML Side-Channel on CiM for Input Reconstruction + (Wang, Ziyu, et al. "PowerGAN: a machine learning approach for power side‐channel attack on compute‐in‐memory accelerators." Advanced Intelligent Systems 5.12 (2023): 2300313.)
Detection of smart cars cyber attacks + (Weber et al: Embedded Hybrid Anomaly Detection for Automotive CAN Communication, Weber et al: Online Detection of Anomalies in Vehicle Signals using Replicator Neural Networks)
Comparative study of an automated testing coverage for a TCP/IP stack implementation + (Wojciech Mostowski, Thomas Arts, and John … Wojciech Mostowski, Thomas Arts, and John Hughes. Modelling of Autosar Libraries for Large Scale Testing. Proceedings, 2nd Workshop on Models for Formal Analysis of Real Systems (MARS 2017), Uppsala, Sweden, April 2017, Volume 244 of EPTCS. http://ceres.hh.se/mediawiki/images/b/bb/Mostowski_mars2017.pdfThomas Arts and John Hughes (2016): How Well are Your Requirements Tested? In: 2016 IEEE International Conference on Software Testing, Verification and Validation, pp. 244–254, doi:10.1109/ICST.2016.23.on, pp. 244–254, doi:10.1109/ICST.2016.23.)
Name of the new projectEstimating agricultural development indicators over large areas from satellite images – an approach using convolutional neural networks and transfer learning + (Xie, M., N. Jean, M. Burke, D. Lobell & … Xie, M., N. Jean, M. Burke, D. Lobell & S. Ermon (2015) Transfer learning from deep features for remote sensing and poverty mapping. arXiv preprint arXiv:1510.00098.Jean, N., M. Burke, et al (2016) Combining satellite imagery and machine learning to predict poverty. Science, 353, 790-794.ing to predict poverty. Science, 353, 790-794.)
Peer Group Discovery in District Heating Substations and Heat Pumps for Self-Monitoring + (Y. Kim and S. Sohn, "Stock fraud detection … Y. Kim and S. Sohn, "Stock fraud detection using peer group analysis", Expert Systems with Applications, vol. 39, no. 10, pp. 8986-8992, 2012.D. Weston, D. Hand, N. Adams, C. Whitrow and P. Juszczak, "Plastic card fraud detection using peer group analysis", Advances in Data Analysis and Classification, vol. 2, no. 1, pp. 45-62, 2008.D. Weston, N. Adams, Y. Kim and D. Hand, "Fault Mining Using Peer Group Analysis", Challenges at the Interface of Data Analysis, Computer Science, and Optimization, pp. 453-461, 2012.ence, and Optimization, pp. 453-461, 2012.)
Leveraging LLMs for Clinical Note Annotation and Uncertainty Estimation + (Yang, Zhichao, et al. "Multi-label few-sho … Yang, Zhichao, et al. "Multi-label few-shot ICD coding as autoregressive generation with prompt." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 37. No. 4. 2023.Liu, Leibo, et al. "Automated icd coding using extreme multi-label long text transformer-based models." Artificial Intelligence in Medicine (2023): 102662.Hu, Edward J., et al. "Lora: Low-rank adaptation of large language models." arXiv preprint arXiv:2106.09685 (2021).Sensoy, Murat, Lance Kaplan, and Melih Kandemir. "Evidential deep learning to quantify classification uncertainty." Advances in neural information processing systems 31 (2018). information processing systems 31 (2018).)
Piglets Detection and Counting using Deep Neural Networks + (Yolo: https://pjreddie.com/darknet/yolo/)
Social touch for robots + (You can read some papers by Breazeal and Dautenhahn about social robots.)
Quantifying exercise-induced muscle fatigue by machine learning + (Yousif, Hayder A., et al. "Assessment of m … Yousif, Hayder A., et al. "Assessment of muscles fatigue based on surface EMG signals using machine learning and statistical approaches: a review." IOP conference series: materials science and engineering. Vol. 705. No. 1. IOP Publishing, 2019.Karlik, Bekir. "Machine learning algorithms for characterization of EMG signals." International Journal of Information and Electronics Engineering 4.3 (2014): 189.Rampichini, S., Vieira, T. M., Castiglioni, P., & Merati, G. (2020). Complexity analysis of surface electromyography for assessing the myoelectric manifestation of muscle fatigue: A review. Entropy, 22(5), 529.Carroll, T. J., Taylor, J. L., & Gandevia, S. C. (2017). Recovery of central and peripheral neuromuscular fatigue after exercise. Journal of Applied Physiology, 122(5), 1068-1076.Yousefi, J., & Hamilton-Wright, A. (2014). Characterizing EMG data using machine-learning tools. Computers in biology and medicine, 51, 1-13.ng tools. Computers in biology and medicine, 51, 1-13.)
Courteous robot guide for visitors to an intelligent home + (Yusuke Kato, Takayuki Kanda, Hiroshi Ishig … Yusuke Kato, Takayuki Kanda, Hiroshi Ishiguro. May I help you? Design of Human-like Polite Approaching Behavior. HRI 2015: 35-42Tomoko Yonezawa, Hirotake Yamazoe, Akira Utsumi, Shinji Abe. Anthropomorphic awareness of partner robot to user’s situation based on gaze and speech detection. International Journal of Autonomous and Adaptive Communications Systems. Volume 5, Issue 1. DOI: 10.1504/IJAACS.2012.044782, Issue 1. DOI: 10.1504/IJAACS.2012.044782)
Data Mining In a Warehouse Inventory + (Zeynep Akata, Florent Perronnin, Zaid Harc … Zeynep Akata, Florent Perronnin, Zaid Harchaoui, Cordelia Schmid. Good Practice in Large-Scale Learning for Image Classi cation. IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2014, 36 (3), pp.507-520.<10.1109/TPAMI.2013.146>.<hal-00835810>Florent Perronnin, Zeynep Akata, Zaid Harchaoui, Cordelia Schmid. Towards Good Practice in Large-Scale Learning for Image Classification. CVPR 2012 - IEEE Computer Vision and Pattern Recognition, Jun 2012, Providence (RI), United States. IEEE, pp.3482-3489, 2012,<10.1109/CVPR.2012.6248090>.<hal-00690014>Raphael Puget, Nicolas Baskiotis, Patrick Gallinari. Sequential Dynamic Classi cation for Large Scale Multi-class Problems. Extreme Classi cation Workshop at ICML, Jul 2015, Lille,France. 2015.<hal-01207428>ion Workshop at ICML, Jul 2015, Lille,France. 2015.<hal-01207428>)
Obstacle Identification from 3D Data for AGVs in a Warehouse Environment + (Zhang, Hao, et al. "SVM-KNN: Discriminativ … Zhang, Hao, et al. "SVM-KNN: Discriminative nearest neighbor classification for visual category recognition." Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on. Vol. 2. IEEE, 2006.Golovinskiy, Aleksey, Vladimir G. Kim, and Thomas Funkhouser. "Shape-based recognition of 3D point clouds in urban environments." Computer Vision, 2009 IEEE 12th International Conference on. IEEE, 2009.Rusu, Radu Bogdan, and Steve Cousins. "3d is here: Point cloud library (pcl)." Robotics and Automation (ICRA), 2011 IEEE International Conference on. IEEE, 2011.Nüchter, Andreas, and Joachim Hertzberg. "Towards semantic maps for mobile robots." Robotics and Autonomous Systems 56.11 (2008): 915-926.Lai, Kevin, and Dieter Fox. "Object recognition in 3D point clouds using web data and domain adaptation." The International Journal of Robotics Research 29.8 (2010): 1019-1037.Brostow, Gabriel J., et al. "Segmentation and recognition using structure from motion point clouds." Computer Vision–ECCV 2008. Springer Berlin Heidelberg, 2008. 44-57.Rusu, Radu Bogdan, et al. "Fast 3d recognition and pose using the viewpoint feature histogram." Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on. IEEE, 2010.Drost, Bertram, et al. "Model globally, match locally: Efficient and robust 3D object recognition." Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on. IEEE, 2010.VPR), 2010 IEEE Conference on. IEEE, 2010.)
Project with chargefinder.com + (http://chargefinder.com/)
Merging Clothoids with B-Splines + (http://en.wikipedia.org/wiki/B-spline http://en.wikipedia.org/wiki/Clothoid)
Evolutionary Behavior Trees for Multi-Agent Task-Oriented Environment + (http://frail.ii.pwr.edu.pl/)
Simulating Crowds for Traffic Safety Research + (http://gamma.cs.unc.edu/research/crowds/ http://www.coppeliarobotics.com/)
Detecting Faults and Estimating Missing Values in Smart Meter Data + (http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5524054 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1425550)
Acumen Robot Model Series + (http://www.acumen-language.org/ http://en.wikipedia.org/wiki/SCARA SCARA)
Evaluation of Open Source Robot Simulators for Smart Mobility Applications + (http://www.gcdc.net/ http://en.wikipedia.o … http://www.gcdc.net/http://en.wikipedia.org/wiki/Research_and_developmenthttp://en.wikipedia.org/wiki/Verification_and_validationhttp://www.robocup.org/http://www.theroboticschallenge.org/aboutsimulator.aspxhttp://www.coppeliarobotics.com/http://gazebosim.org/oppeliarobotics.com/ http://gazebosim.org/)
RaspberryPiVolvoLogger + (http://www.raspberrypi.org/ http://lnxpps.de/rpie/ http://islab.hh.se/mediawiki/index.php/ReDi2Service http://www.youtube.com/watch?v=KJ5hMkWPEGY)
Model Volvo Truck Lifetime Repair History + (http://www.sciencedirect.com/science/artic … http://www.sciencedirect.com/science/article/pii/S000437029800023Xhttp://www.pomdp.org/index.shtmlhttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.7714http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.147.1619http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.8737su.edu/viewdoc/summary?doi=10.1.1.335.8737)
Understand Patterns in Volvo Truck Lifetime Repair History + (http://www.sciencedirect.com/science/artic … http://www.sciencedirect.com/science/article/pii/S000437029800023Xhttp://www.pomdp.org/index.shtmlhttp://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.7714http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.147.1619http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.335.8737su.edu/viewdoc/summary?doi=10.1.1.335.8737)
Human Value Detection + (https://aclanthology.org/2022.acl-long.306.pdf https://www.youtube.com/watch?v=ZAQ4LELCCY4)
Zero-Shot Learning for Semantic Segmentation + (https://arxiv.org/pdf/1707.00600.pdf http … https://arxiv.org/pdf/1707.00600.pdfhttps://static.googleusercontent.com/media/research.google.com/en//pubs/archive/41473.pdfhttps://arxiv.org/pdf/1906.00817.pdfhttps://openaccess.thecvf.com/content_ICCVW_2019/papers/MDALC/Kato_Zero-Shot_Semantic_Segmentation_via_Variational_Mapping_ICCVW_2019_paper.pdfhttps://github.com/daooshee/Few-Shot-Learningps://github.com/daooshee/Few-Shot-Learning)

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