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This page provides a simple browsing interface for finding entities described by a property and a named value. Other available search interfaces include the page property search, and the ask query builder.

List of results

• Road user behavior prediction  + (Road user behavior recognition and manipulation using deep learning)
• Something to do with social robots  + (Robot Exercise Coach)
• Collaboration with Bankomat 4  + (Robustness of LLMs Against Prompt Injection Attacks RQ: What defense mechanisms can mitigate prompt injection vulnerabilities in enterprise LLM deployments?)
• Sandboxed scripting on embedded systems  + (Sandboxed scripting on embedded systems)
• Zenseact Scalable Mapping  + (Scalable mapping through crowd sourcing)
• Segment Routing based on Geographic Checkpoints  + (Segment Routing based on Geographic Checkpoints:)
• Segment-based coordination of Congestion Control  + (Segment-based coordination of Congestion Control)
• Segmentation and object identification in warehouse environments using machine learning  + (Segmentation and object identification in warehouse environments using machine learning)
• Trajectory prediction algorithms for intention sharing in Micromobility  + (Self-prediction of trajectories by Vulnerable Road Users to share their intentions with vehicles.)
• Semantic Analysis of 2D Maps With a Metric-Topological Approach  + (Semantic Analysis of 2D Maps With a Metric-Topological Approach.)
• Sensor fusion and machine learning for drone detection and classification  + (Sensor fusion and machine learning for drone detection and classification)
• Service Centric Mobility Management in LEO Constellations  + (Service Centric Mobility Management in LEO Constellations)
• CoopSim  + (Simulation of cooperative systems behavior in the presence of faults)
• Situation awareness in traffic  + (Situation awareness in traffic)
• Smart sensor  + (Small smart sensors)
• Non-Invasive Safety Monitoring via Integrated Sensing and Communication  + (Smart sensing for motion, presence, and accident detection—without cameras)
• Using Deep Q-Learning (Alpha-Go algorithm) to solve routing problems in warehouse logistics  + (Solving the famous vehicle-routing problem using Deep Q-Learning)
• Bowling: human motion quantification + ball quantification  + (Study visual parameters to quantify human and ball motion, aiming to be better bowling player)
• One dimensional frequency decomposition of oriented local images applied to fingerprints  + (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.)
• Transfer Learning for Machine Diagnosis and Prognosis  + (Study and develop deep adversarial neural networks (DANN) based methods to detect faults and predict failures in industrial equipment, under transfer learning scenarios.)
• Comprehending low-dimensional manifolds of temporal data from the home  + (Study and development of tools and methods for the visualization of (temporal) human activity patterns.)
• Transfer Learning for Network Security  + (Study of Transfer Learning techniques in Network Security applications- Network Traffic Classification and Intrusion Detection)
• On control of robots in remote workspaces using lasers  + (Supervised autonomy for controlling robots at remote locations. Lasers and ultrasonic ranging to be used.)
• Improving Time-series Generative Adversarial Networks (GANs) for Generating Electronic Health Records (EHRs)  + (Synthetic Electronic Health Records)
• Conditional GAN for better embedding and generation of medical codes  + (Synthetic data generation of Electronic Health Records with a focus on medical codes)

• Project with Whole AB  + (TBD)

• Smart City Monitoring Using Ontology-based Machine Learning  + (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)
• Deep Networks for Semantic Scene Understanding  + (The candidate will implement a neural network to detect spatial relations between objects in the scene. For instance, the book is on the table or the spoon is in the cup.)
• The healthcare data mining with advance AI technology  + (The cardiovascular health care project)
• Investigation of spread spectrum techniques to reduce the electromagnetic interference in switch mode power supply  + (The goal of the project is to investigate spread-spectrum-based PWM techniques to reduce the EMI in motor drivers caused by the SMPS)
• Resilience of ML Hardware Accelerators Against Accuracy Degrading Trojans  + (The goal of this project is to assess the resilience of machine learning (ML) hardware accelerators, with a specific focus on Convolutional Neural Network (CNN) accelerators, when subjected to Trojan attacks aimed at degrading their accuracy.)
• Modelling Health Recommender System using Hybrid Techniques  + (The goal of this project is to develop a health recommender system using existing machine learning techniques.)
• Embedding DNN models on mobile robots for object detection  + (The idea in this project is to employ transfer learning methods to teach a mobile robot to detect a handful of everyday objects in the real-world environment, and investigate the challenges and difficulties that are faced to this end)
• Graph Neural Networks for Traffic Flow Forecasting  + (The main goal of this project is to explore GNN for traffic flow forecasting)
• Graph Neural Networks for cardiovascular disease  + (The main goal of this project is to explore GNN for cardiovascular disease)
• Positioning of the user at the HINT  + (The positioning of the user at the Halmstad intelligent home (HINT).)
• Multi-robot coordination in a warehouse  + (The project aims to coordinate motion of multiple robots to accomplish a single task)
• Gait analysis using wearable sensors in Parkinson's disease  + (The project aims to develop a machine learning tool for the assessment of Parkinsonian gait in a natural environment)
• Transfer Learning by Selection of Invariant Features  + (The project aims to develop novel methods to identify invariant features to transfer across multiple domains.)
• Convolutional Neural Network (CNN) features behaviour in the context of textures  + (The project aims to quantify the behaviour of Convolutional Neural Network (CNN) features in the context of textures.)
• Digit recognition by lip-movements and time recursive Neural Networks  + (The project aims to recognize digits by lip movements and neural networks)
• Project with Atos  + (The project involves the development of software for the TrueDepth technology of the iPhone.)
• Machine Learning-based optimization of physical activity  + (The project should be able to detect the difference between the current exercise and a reference version of the exercise.)
• The CatFish project  + (The project within Innovation Lab called CatFish has the aim of collecting data from water bodies through a system of drones)
• Non-contact estimation of blood pressure using photoplethysmography  + (The proposal aims to develop a camera-based system for estimating blood pressure using machine learning and photoplethysmography)
• Deep neural network optimization for path prediction in vessels!  + (The purpose of this thesis is analyzing a ferry dataset to identify the most optimal path using deep-net.)
• Evaluating the Effects of Social Media on Educational Sustainability in Sweden  + (The research analyzes sentiment in social media data related to educational sustainability practices and outcomes in Sweden.)
• Multitask Learning in Autonomous Driving  + (The student should annotate 3D point cloud data for semantic segmentation and object detection. A new deep learning model needs to be implemented to learn both tasks.)
• Uncertainty quantification for data driven clinical decision making  + (The student will build upon the field of evidential deep learning to identify and understand when the model says 'I don't know')
• Multivariate Time Series Analysis with Irregularly Sampled Data  + (The student will devise methods for handling irregularly sampled multivariate time series data, addressing missing data and modeling temporal relationships for applications in healthcare)
• Leveraging LLMs for Clinical Note Annotation and Uncertainty Estimation  + (The student will investigate the potential of LLMs to simplify clinical note annotation along with uncertainty estimation, contributing to improved healthcare data management.)