Lennart Svensson
Lennart Svensson is Professor in Signal Processing. His research interests include nonlinear filtering, multi-target tracking, deep learning, Bayesian inference and reinforcement learning.
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Showing 163 publications
Are NeRFs ready for autonomous driving? Towards closing the real-to-simulation gap
LidarCLIP or: How I Learned to Talk to Point Clouds
Experimental Validation of Single BS 5G mmWave Positioning and Mapping for Intelligent Transport
On the connection between Noise-Contrastive Estimation and Contrastive Divergence
Set-Type Belief Propagation with Applications to Poisson Multi-Bernoulli SLAM
Markov Chain Monte Carlo Multi-Scan Data Association for Sets of Trajectories
Improving Open-Set Semi-Supervised Learning with Self-Supervision
Active Learning with Weak Supervision for Gaussian Processes
Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation
MmWave Mapping and SLAM for 5G and Beyond
Deep Fusion of Multi-Object Densities Using Transformer
Deep Learning for Model-Based Multi-Object Tracking
Masked Autoencoder for Self-Supervised Pre-Training on Lidar Point Clouds
Integrated Monostatic and Bistatic mmWave Sensing
Deep Learning for Model-Based Multiobject Tracking
You can have your ensemble and run it too - Deep Ensembles Spread Over Time
Generalised Active Learning With Annotation Quality Selection
Doppler Exploitation in Bistatic mmWave Radio SLAM
A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM
Object Detection as Probabilistic Set Prediction
Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering
Multiple Object Trajectory Estimation Using Backward Simulation
A comparison between PMBM Bayesian track initiation and labelled RFS adaptive birth
Experimental Validation of Single Base Station 5G mm Wave Positioning: Initial Findings
PMBM-Based SLAM Filters in 5G mmWave Vehicular Networks
DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision
Iterated Posterior Linearization PMB Filter for 5G SLAM
Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning
Extended Object Tracking Using Sets of Trajectories with a PHD Filter
A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
A time-weighted metric for sets of trajectories to assess multi-object tracking algorithms
Lidar–camera semi-supervised learning for semantic segmentation
An Uncertainty-Aware Performance Measure for Multi-Object Tracking
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning
DACS: Domain adaptation via cross-domain mixed sampling
5G SLAM with Low-complexity Channel Estimation
Trajectory multi-Bernoulli filters for multi-target tracking based on sets of trajectories
Multiple Target Tracking Based on Sets of Trajectories
Deep LiDAR localization using optical flow sensor-map correspondences
Exploiting Diffuse Multipath in 5G SLAM
5G SLAM Using the Clustering and Assignment Approach with Diffuse Multipath
Backward simulation for sets of trajectories
Trajectory Poisson Multi-Bernoulli Filters
Poisson Multi-Bernoulli Mixture Conjugate Prior for Multiple Extended Target Filtering
Extended Object Tracking with Automotive Radar Using Learned Structural Measurement Model
A general framework for ensemble distribution distillation
Spatiotemporal Constraints for Sets of Trajectories with Applications to PMBM Densities
Levenberg-Marquardt and Line-Search Extended Kalman Smoothers
Spooky effect in optimal OSPA estimation and how GOSPA solves it
LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks
Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories
Gaussian implementation of the multi-Bernoulli mixture filter
Bayesian Linear Regression on Deep Representations
Trajectory PHD and CPHD filters
Multiscan implementation of the trajectory poisson multi-Bernoulli mixture filter
Damped Posterior Linearization Filter
An Implementation of the Poisson Multi-Bernoulli Mixture Trajectory Filter via Dual Decomposition
Likelihood-Based Data Association for Extended Object Tracking Using Sampling Methods
Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and Implementation
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation
Poisson Multi-Bernoulli Mixture Trackers: Continuity Through Random Finite Sets of Trajectories
Cooperative Localization Using Posterior Linearization Belief Propagation
Trajectory probability hypothesis density filter
Pedestrian tracking using Velodyne data-Stochastic optimization for extended object tracking
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling
Imitation Learning for Vision-based Lane Keeping Assistance
Fast LIDAR-based road detection using fully convolutional neural networks
Performance evaluation of multi-bernoulli conjugate priors for multi-target filtering
Generalized optimal sub-pattern assignment metric
LIDAR-based Driving Path Generation Using Fully Convolutional Neural Networks
Iterated Posterior Linearization Smoother
Recent Results on Bayesian Cramer-Rao Bounds for Jump Markov Systems
Gamma Gaussian inverse-Wishart Poisson multi-Bernoulli filter for extended target tracking
Labeling Uncertainty in Multitarget Tracking
Poisson multi-Bernoulli filter for extended object tracking
Variational Bayesian Expectation Maximization for Radar Map Estimation
Poisson Multi-Bernoulli Radar Mapping Using Gibbs Sampling
On the relation between Gaussian process quadratures and sigma-point methods
Recent results on Bayesian Cramér-Rao bounds for jump Markov systems
Long-range road geometry estimation using moving vehicles and road-side observations
A batch algorithm for estimating trajectories of point targets using expectation maximization
Posterior Linearization Filter: Principles and Implementation Using Sigma Points
Gaussian MAP Filtering Using Kalman Optimization
Infinite Factorial Dynamical Model
Flipping a PhD course using movies from a MOOC
Adaptive unscented Gaussian likelihood approximation filter
Designing and Evaluating a Flipped Signals and Systems Course
Variational Bayesian EM for SLAM
A Bayesian nonparametric approach for blind multiuser channel estimation
Bayesian Road Estimation Using Onboard Sensors
Vehicle self-localization using off-the-shelf sensors and a detailed map
Gaussian process quadratures in nonlinear sigma-point filtering and smoothing
The Marginal Enumeration Bayesian Cramer-Rao Bound for Jump Markov Systems
Iterated statistical linear regression for Bayesian updates
Two-filter Gaussian mixture smoothing with posterior pruning
Road Geometry Estimation Using a Precise Clothoid Road Model and Observations of Moving Vehicles
Merging-based forward-backward smoothing on Gaussian mixtures
A fresh look at Bayesian Cramér-Rao bounds for discrete-time nonlinear filtering
Target tracking based on estimation of sets of trajectories
A CPHD Filter for Tracking With Spawning Models
Adaptive Stopping for Fast Particle Smoothing
Particle PHD forward filter-backward simulator for targets in close proximity
Smoothed probabilistic data association filter
A CPHD filter for tracking with spawning models - including a FISST based derivation
A Study of MAP Estimation Techniques for Nonlinear Filtering
A map based estimator for inverse complex covariance matricies
Variational Bayesian Framework for Receiver Design in the Presence of Phase Noise in MIMO Systems
Adaptive Radar Sensor Model for Tracking Structured Extended Objects
Moment Estimation Using a Marginalized Transform
Optimal posterior density approximation for bearings-only tracking
A Bayesian look at the optimal track labelling problem
A cardinality preserving multitarget multi-Bernoulli RFS tracker
The Rao-Blackwellized marginal M-SMC filter for Bayesian multi-target tracking and labelling
Extended Object Tracking using a Radar Resolution Model
Marginalized sigma-point filtering
Set JPDA Filter for Multitarget Tracking
An approximate minimum MOSPA estimator
Interpolation based on stationary and adaptive AR(1) modeling
A New Vehicle Motion Model for Improved Predictions and Situation Assessment
Optimal parameterization of posterior densities using homotopy
CS versus MAP and MMOSPA for Multi-Target Radar AOAs
The multitarget Set JPDA filter with target identity
A look at Gaussian mixture reduction algorithms
The Set IMMJPDA filter for multitarget tracking
Bayesian Data Fusion for Distributed Target Detection in Sensor Networks
The JPDAF in practical systems: computation and snake oil
Shooting two birds with two bullets: how to find Minimum Mean OSPA estimates
A New Multiple Model Filter with Switch Time Conditions
Set JPDA Filter for Multi-Target Tracking
On the Bayesian Cramér-Rao Bound for Markovian Switching Systems
The Reference Prior for Complex Covariance Matrices With Efficient Implementation Strategies
Set JPDA algorithm for tracking unordered sets of targets
Set JPDA Algorithm for Tracking Sonar Crossing Targets
Performance Evaluation of MHT and GM-CPHD in a Ground Target Tracking Scenario
Evaluating the Bayesian Cramér-Rao Bound for multiple model filtering
An Alternative Derivation of the Cardinalized Probability Hypothesis Density Filter
Coordinate transformations and implementation details for a new vehicle motion model
Tracking vehicles using radar detections
Multiple Model Filtering with Switch Time Conditions
Joint driver intention classification and tracking of vehicles
A New motion model for tracking of vehicles
On Posterior Distributions for Signals in Gaussian Noise With Unknown Covariance Matrix
The Haar measure and the generation of random unitary matrices
Estimating complex covariance matrices
Dual-Band Land Mine Detection Using a Bayesian Approach
Analytical Expression for the Posterior Distribution of Signals in Colored Gaussian Noise
Land Mine Detection in Rotationally Invariant Noise Fields
Infrared Detection of Buried Land Mines Based on Texture Modeling
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Showing 11 research projects
Deep MultiModal Learning for Automotive Applications
Deep multi-object tracking for self-driving vehicles
6G Artificial Intelligence Radar
Semi-supervised Learning for Medical Image Analysis
Robust and precise Semi-Supervised Learning schemes
Probabilistic models and deep learning - bridging the gap
Deep multi-object tracking for ground truth trajectory estimation
Target tracking in complex scenarios including jamming conditions for airborne sensor systems
Fordonspositionering och ruttprediktion
Parameter estimation based on sparse modeling
Model-based Reconstruction and Classification Based on Near-Field Microwave Measurements