| A machine learning approach for biomass characterization MU Ahmed, P Andersson, T Andersson, ET Aparicio, H Baaz, S Barua, ... Energy Procedia 158, 1279-1287, 2019 | 21 | 2019 |
| Bluetooth low energy and smartphones for proximity-based automatic door locks T Andersson | 20 | 2014 |
| Comparison of machine learning’s-and humans’-ability to consistently classify anomalies in cylinder locks T Andersson, M Bohlin, T Olsson, M Ahlskog IFIP International Conference on Advances in Production Management Systems …, 2022 | 3 | 2022 |
| Road boundary detection using ant colony optimization algorithm T Andersson, A Kihlberg, A Sundström, N Xiong Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery …, 2020 | 3 | 2020 |
| Sample size prediction for anomaly detection in locks T Andersson, M Ahlskog, T Olsson, M Bohlin Procedia CIRP 120, 870-874, 2023 | 2 | 2023 |
| Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy-A Machine Learning Approach MU Ahmed, P Andersson, T Andersson, ET Aparicio, H Baaz, S Barua, ... 10th International Conference on Applied Energy (ICAE2018), 2018 | 2 | 2018 |
| DIFFERENTIAL DRIVE ROBOTPLATFORM WITH EXTERNALFORCE SENSING CAPABILITIES INTENDED FOR LOGISTICAL TASKS SET IN A HOSPITAL ENVIRONMENT T Andersson, A Kihlberg | 1 | 2020 |
| Automated Tactile Sensing for Quality Control of Locks Using Machine Learning T Andersson Mälardalens universitet, 2024 | | 2024 |
| Interpretable ML model for quality control of locks using counterfactual explanations T Andersson, M Bohlin, M Ahlskog, T Olsson 2024 8th International Conference on Artificial Intelli-gence, Automation …, 2024 | | 2024 |
| Interpretable machine learning model for quality control of locks using counterfactual explanations T Andersson, M Ahlskog, M Bohlin, T Olsson | | |
