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From ISLAB/CAISR
| Supervisors | OneLineSummary | |
|---|---|---|
| Modelling behavior and interaction of road users in transportation systems | Björn Åstrand Cristofer Englund |
Modelling behavior and interaction of road users in transportation systems |
| Modelling vehicles'/drivers' behaviour using LVD | Reza Khoshkangini | Modeling the bahevaior of the vehicles/drivers exploiting the vehicles usage in different context. |
| Multi-robot coordination in a warehouse | Jennifer David Björn Åstrand |
The project aims to coordinate motion of multiple robots to accomplish a single task |
| Multi-robot trajectory adaptation using a state-time elastic band approach | Roland Philippsen Jennifer David |
For teams of robots moving through dynamic environments, deform planned trajectories in space and time such that they remain collision-free and reach the goal (if possible) or report failure if replanning is needed. |
| NOMAD | Thorsteinn Rögnvaldsson Stefan Byttner |
Nonlinear methods for accurate deviation detection (NOMAD) |
| Name of the new projectEstimating agricultural development indicators over large areas from satellite images – an approach using convolutional neural networks and transfer learning | Mattias Ohlsson Thorsteinn Rögnvaldsson |
In this project you will use deep learning models, specifically convolutional neural networks (CNN), to analyze satellite imagery to estimate agricultural development indicators. |
| Object Detection for Autonomous Vehicles | Eren Erdal Aksoy | Implementing a single-stage deep network to detect vehicles in the segmented 3D LiDAR point cloud |
| Object Movement Prediction for Autonomous Cars | Tiago Cortinhal | Predicting the movement of objects in the context of autonomous cars |
| On control of robots in remote workspaces using lasers | Björn Åstrand Jennifer David |
Supervised autonomy for controlling robots at remote locations. Lasers and ultrasonic ranging to be used. |
| On detecting deviations by autonomously discovering district heating control strategy used by buildings | Shiraz Farouq Sławomir Nowaczyk |
autonomously detect control strategy and building type from district heating data |
| One dimensional frequency decomposition of oriented local images applied to fingerprints | Josef Bigun | Study and develop 1D continuous frequency fitting of a predetermined number of (oriented) sinusoids to images which are strongly oriented locally, in particular forensic fingerprints. |
| Pallet Detection and Mapping | Björn Åstrand Saeed Gholami Shahbandi |
Pallet Detection and Mapping in a Warehouse Environment |
| Peer Group Discovery in District Heating Substations and Heat Pumps for Self-Monitoring | Ece Calikus Sławomir Nowaczyk |
Finding suitable peer groups to represent district heating and heat pump customers |
| Piglets Detection and Counting using Deep Neural Networks | Peter Berck Sepideh Pashami |
Piglets Detection and Counting using Deep Neural Networks |
| Positioning of the user at the HINT | Abbas Orand & Per Sandrum | The positioning of the user at the Halmstad intelligent home (HINT). |
| Prediction of neurodegenerative disorders based on brain images | Farzaneh Etminani Stefan Byttner |
prediction of neurodegenerative disorders based on brain images using deep learning algorithms |
| Protecting bikers in traffic by computer vision | Josef Bigun | Protecting bikers in traffic by computer vision |
| Real-time Motion Analysis using Inertial Sensors | Siddhartha Khandelwal Nicholas Wickström |
Develop a real-time (online) algorithm that can detect walking events from accelerometer signals. |
| Recognition of Human Intentions for Automated Cars | Cristofer Englund Sławomir Nowaczyk |
Recognition of Human Intentions for Automated Cars |
| Recognition of logotypes and signs in photos | Josef Bigun | Recognizing man-made 2D objects such as logotypes in photos of human environments |
| Reinforcement learning for End-to-End autonomous driving | Cristofer Englund Alexey Voronov Nicholas Wickström |
By using image data as input, and the vehicle steering and acceleration as output control signals, investigate how machine learning can control a vehicle. |
| Replacements vs repairs. What is really a breakdown from the point of view of the data? | Pablo del Moral Sławomir Nowaczyk |
Finding ways to test how similar or different are the actions performed on a faulty machine. How does the effect of an intervention on the machine affect the data? |
| Representation Learning for Deviation Detection | Sławomir Nowaczyk Yuantao Fan |
Optimise Echo State Networks for time series forecasting and reconstruction. Propose methods, e.g. objective functions, to train Echo State Networks for deviation detection |
| Resolving Class Imbalance using Generative Adversarial Networks | Sepideh Pashami Peter Berck |
Resolving Class Imbalance using Generative Adversarial Networks |
| Safe deployment of Deep Neural Networks in automotive engineering | Cristofer Englund Sepideh Pashami |
Evaluation of DNN factors with respect to robustness in safety critical systems. |
| Safety assurance for human in automated crane environment | Björn Åstrand Josef Bigun |
safety assurance for human in automated crane environment |
| Segmentation and object identification in warehouse environments using machine learning | Björn Åstrand Naveed Muhammad |
Segmentation and object identification in warehouse environments using machine learning |
| Segmentation of shoeprints | Anna Mikaelyan Josef Bigun |
Finding boundaries of homogeneous regions in shoeprint images |
| Self-adaptive Recommender System In Conditional Context | Reza Khoshkangini | In this project we intend to develop an adaptive system that can adapt itself --based on different context-- at providing service to conditional preference of users which change over time. |
| Short-Term Energy Demand Forecasting | Anita Sant'Anna Sławomir Nowaczyk Hassan Mashad Nemati |
Forecasting the electricity consumption based on historical usage by using smart meter data |
| Smart App for PD | Anita Sant'Anna | A smart-watch app for monitoring symptoms in Parkinson's Disease |
| Smart City Monitoring Using Ontology-based Machine Learning | Sławomir Nowaczyk Ece Calikus |
The aim of this project is to create ontology-based supervised and unsupervised machine learning methods for self monitoring to improve reliability of complex environments in smart cities |
| Smart meters' data analysis | Hassan Mashad Nemati Sławomir Nowaczyk |
Customer characterization, customer classification and anomaly detection |
| Something to do with social robots | Martin Cooney Eren Erdal Aksoy Fernando Alonso-Fernandez |
Robot Exercise Coach |
| Speaker/speech recognition and engagement | Taha Khan Oskar Lundgren |
Algorithms, sensors and devices for recognizing speaker as well as spoken words and engagement from an arbitrary number of people in a conversation |
| Thermal Profiling of Residential Energy Consumption for Heat Pump and District Heating Customers | Ece Calikus Sławomir Nowaczyk |
Finding interesting patterns of heat pump and district heating customers in order to identify meaningful thermal profiles |
| Transfer Learning for Machine Diagnostics and Prognostics | Yuantao Fan Sepideh Pashami Mohammad Ghaith Altarabichi |
Develop a deep adversarial neural networks (DANN) based method to predict failures and estimate machine health, under transfer learning settings. |
| Understand Patterns in Volvo Truck Lifetime Repair History | Sławomir Nowaczyk Sepideh Pashami Fredrik Moeschlin (at Volvo) |
A project in collaboration with Volvo AB on finding good representations for data-driven description of Volvo truck's repair and maintenance history |
| Understanding Applicability of Echo State Networks to Diverse Industrial Data | Shiraz Farouq Sławomir Nowaczyk |
Understanding the Governing Dynamics of Echo State Networks (ESN) on time varying signals (in terms of properties) from different industry sources. |
| Understanding usage of Volvo trucks | Sławomir Nowaczyk Fredrik Moeschlin (at Volvo) |
A project in collaboration with Volvo AB on understanding vehicle usage patterns. |
| Using Deep Q-Learning (Alpha-Go algorithm) to solve routing problems in warehouse logistics | Jennifer David Thorsteinn Rögnvaldsson |
Solving the famous vehicle-routing problem using Deep Q-Learning |
| Value of BIG DATA for Large Building Owners | Sepideh Pashami | It is an explanatory project with a company called Mutual Benefits Engineering AB |
| Wisdom of the crowd, is there a single crowd? | Pablo del Moral Sławomir Nowaczyk |
Finding different clusters of machines based on their behavior as a first step towards anomaly detection and predictive maintenance. |
