Browsing Mathematics (Faculty of) by Supervisor "Czarnecki, Krzysztof"
Now showing items 1-20 of 26
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3D Online Multi-Object Tracking for Autonomous Driving
(University of Waterloo, 2019-08-29)This research work focuses on exploring a novel 3D multi-object tracking architecture: 'FANTrack: 3D Multi-Object Tracking with Feature Association Network' for autonomous driving, based on tracking by detection and online ... -
Accelerating the Training of Convolutional Neural Networks for Image Segmentation with Deep Active Learning
(University of Waterloo, 2020-01-23)Image semantic segmentation is an important problem in computer vision. However, Training a deep neural network for semantic segmentation in supervised learning requires expensive manual labeling. Active learning (AL) ... -
An Application of Out-of-Distribution Detection for Two-Stage Object Detection Networks
(University of Waterloo, 2020-02-14)Recently, much research has been published for detecting when a classification neural network is presented with data that does not fit into one of the class labels the network learned at train time. These so-called ... -
Autonomous Vehicles with Visual Signals for Pedestrians: Experiments and Design Recommendations
(University of Waterloo, 2020-01-23)Autonomous Vehicles (AV) are the future of transportation and they will transform the dynamic of vehicle and pedestrian interaction. However, in the absence of a driver, it is not clear how an AV can use visual signals to ... -
ClaferMPS: Modeling and Optimizing Automotive Electric/Electronic Architectures Using Domain-Specific Languages
(University of Waterloo, 2017-01-23)Modern automotive electric/electronic (E/E) architectures are growing to the point where architects can no longer manually predict the effects of their design decisions. Thus, in addition to applying an architecture reference ... -
Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving
(University of Waterloo, 2020-01-24)The behaviour planning subsystem, which is responsible for high-level decision making and planning, is an important aspect of an autonomous driving system. There are advantages to using a learned behaviour planning system ... -
Computational Methods for Combinatorial and Number Theoretic Problems
(University of Waterloo, 2017-04-27)Computational methods have become a valuable tool for studying mathematical problems and for constructing large combinatorial objects. In fact, it is often not possible to find large combinatorial objects using human ... -
Dynamic-Occlusion-Aware Risk Identification for Autonomous Vehicles Using Hypergames
(University of Waterloo, 2021-12-17)A particular challenge for both autonomous vehicles (AV) and human drivers is dealing with risk associated with dynamic occlusion, i.e., occlusion caused by other vehicles in traffic. In order to overcome this challenge, ... -
Empirical Game Theoretic Models for Autonomous Driving: Methods and Applications
(University of Waterloo, 2022-09-16)In recent years, there has been enormous public interest in autonomous vehicles (AV), with more than 80 billion dollars invested in self-driving car technology. However, for the foreseeable future, self-driving cars will ... -
Expert System and a Rule Set Development Method for Urban Behaviour Planning
(University of Waterloo, 2020-05-15)Today, autonomous vehicles have the capacity to achieve fully autonomous driving in predefined environments. This ability can be in part attributed to advancements in motion planning, which plans the vehicle’ behaviours ... -
A Hierarchical Pedestrian Behaviour Model to Reproduce Realistic Human Behaviour in a Traffic Environment
(University of Waterloo, 2022-03-07)Understanding pedestrian behaviour in traffic environments is a crucial step in the development and testing of autonomous vehicles. As the environment's most vulnerable road users, pedestrians introduce an element of ... -
Local and Cooperative Autonomous Vehicle Perception from Synthetic Datasets
(University of Waterloo, 2019-09-23)The purpose of this work is to increase the performance of autonomous vehicle 3D object detection using synthetic data. This work introduces the Precise Synthetic Image and LiDAR (PreSIL) dataset for autonomous vehicle ... -
Meta-learning Performance Prediction of Highly Configurable Systems: A Cost-oriented Approach
(University of Waterloo, 2016-04-27)A key challenge of the development and maintenance of configurable systems is to predict the performance of individual system variants based on the features selected. It is usually infeasible to measure the performance of ... -
MLOD: A multi-view 3D object detection based on robust feature fusion method
(University of Waterloo, 2019-09-19)This thesis presents Multi-view Labelling Object Detector (MLOD). The detector takes an RGB image and a LIDAR point cloud as input and follows the two-stage object detection framework. A Region Proposal Network (RPN) ... -
Modeling and Reasoning with Multisets and Multirelations in Alloy
(University of Waterloo, 2017-01-17)Multisets and multirelations arise naturally in modeling; however, most modeling languages either have limited or completely lack support for multisets and multirelations. Alloy, for instance, is a lightweight relational ... -
Modeling the Effects of AUTOSAR Overhead on Automotive Application Software Timing and Schedulability
(University of Waterloo, 2016-10-14)AUTOSAR (AUTomotive Open System ARchitecture) provides an open and standardized E/E architecture to support modularity, transferability, reusability and scalability of the various components required to implement a function ... -
Passenger Response to Driving Style in an Autonomous Vehicle
(University of Waterloo, 2019-09-23)Despite rapid advancements in automated driving systems (ADS), current human-computer interaction research tends to focus more on the safety driver in lower level vehicles. The future of automated driving lies in higher ... -
Policy Extraction via Online Q-Value Distillation
(University of Waterloo, 2019-08-27)Recently, deep neural networks have been capable of solving complex control tasks in certain challenging environments. However, these deep learning policies continue to be hard to interpret, explain and verify which limits ... -
Quantitative Analyses of Software Product Lines
(University of Waterloo, 2022-01-18)A software product-line (SPL) is a family of related software systems that are jointly developed and reuse a set of shared assets. Each individual software system in an SPL is called a software product and includes a set ... -
Safety-Oriented Stability Biases for Continual Learning
(University of Waterloo, 2020-01-24)Continual learning is often confounded by “catastrophic forgetting” that prevents neural networks from learning tasks sequentially. In the case of real world classification systems that are safety-validated prior to ...