Department of Computer Science

MAS Hall of Fame

These are our successful graduates of the Master of Autonomous Systems. The list is constantly being expanded. We are happy to accept additions, especially from previous years.

Master Thesis Defense 2024

  • Quantitative Comparison of Deep Learning Classifiers and Human Attention in Assessing Rare Disorders
  • Increasing Efficiency of Monte-Carlo Tree Search via Bayesian Optimization

Master Thesis Defense 2023

  • Towards Building a Tomato Crop Localization Map using GPS, IMU, and Visual Odometry
  • 3-D Molecular Conformation Generation Using Machine Learning
  • An Investigation into the Impact of Multimodality on Named Entity Recognition
  • Multimodal Deep Learning-Based Adaptation of Robot Behaviour for Assistive Robotics
  • Applying the Principles of YOLO Object Detector to Timeseries Subsequence Search
  • Pedestrian Activity Monitoring using DeepSORT under Partial Occlusions
  • Multi-modal Emotion Categorization in Oral History Interviews
  • Timetable Optimization With the Help of Reinforcement Learning
  • Time series forecasting models for a simulation-accelerating surrogate model
  • Vehicular In-Cabin Depth Estimation Using Sparse Training Data
  • Deepfakes in Style: Improving Face-swapping Autoencoder with StyleGAN Components
  • Continual Learning in Object Detection
  • Benchmark for Few-Shot 6D Pose Estimation Methods
  • On the Explainability of Neural Network Models to Classify Rare Genetic Syndromes from Frontal Facial Images
  • Vision-Based Automation System to Prepare Harvested Lettuces for Packaging
  • Comparative Evaluation of Feature Extraction Methods for Time Series Classification
  • Property-Based Testing: Formalized Robotic Testing for Standard Compliance
  • Multi-View Temporal Fusion in Semantic Segmentation
  • Computer Assisted Short Answer Grading with Rubrics using Active Learning
  • Comparative analysis of the use of different granularity levels on word embeddings for literature-based knowledge discovery
  • End-to-End Prediction of Driving Commands Using 3D Lane Detection as an Auxiliary Task
  • Continuous Control of Under-Actuated Autonomous Vehicles using Reinforcement Learning Methods
  • Navigation of Bulky Robots in Confined Indoor Spaces

Master Thesis Defense 2022

  • Lifelong Action Learning for Socially Assistive Robots
  • Multi-Person Tracking using Generative Models
  • A Neuromorphic Approach to Obstacle Avoidance in Robot Manipulation
  • Composing Software Architectures for Smart Manipulation Tasks based on the Popov-Vereshchagin Hybrid Dynamics Solver
  • Specifying and Generating Simulated Environments for Verifying Autonomous Mobile Robot Scenarios
  • Uncertainty in Explanation methods for Neural Networks
  • COINS Map: Composable ontology-based indoor semantic map
  • Out-of-Distribution Detection in 3D Semantic Segmentation
  • Empirical evaluation of multi-modal communication between a visually impaired person and an autonomous navigation aid
  • Continual Learning in Semantic Segmentation
  • Learning simulation for plastic sheet extrusion in blow molding machine
  • Novelty Detection in Semantic Segmentation
  • Benchmarking Out Of Distribution Detection Methods in 2D Object Detection
  • DExT: Detector Explanation Toolkit for Explaining Multiple Detections Using Saliency Methods
  • Primitive detection on RGB-D data for a compact hybrid scene representation
  • Multisensor data fusion techniques for mass imbalance detection in wind turbine blades
  • Image Based Quality Control in Thermoplastic Composite Production using Deep Transfer Learning
  • Improving Hazardous Scenarios Traceability for Multi-Robot Systems using Knowledge Graph
  • LiDAR-based indoor localization with optimal particle filters using surface normal constraints
  • Auto-Encoding of Semantic Models of Mobile Robot Environment Based on Ontology for Localization and Navigation
  • Self-supervised Learning for Sonar Images: Enhancing Multimodal Perception for Underwater Applications
  • Evaluation of Drift Detection Techniques for Automated Machine Learning Pipelines
  • Object Detection in Dense Volume Data

Master Thesis Defense 2021 

  • Context-based navigation using composed behaviours
  • Humanoid Robot Grasp Suggestion
  • Visuomotor Policy Learning for Predictive Manipulation
  • Resilience of Edge-optimized CNNs to Adversarial Attacks
  • A Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning
  • Effective Neighborhood Feature Exploitation in Graph CNNs for Point Cloud Object-Part Segmentation
  • CoLe-VIO: Supervised Complementary Learning of Keyframe Detection and Visual-Inertial Odometry
  • Improving PySpark Performance with Cross-Language Optimization
  • Design and Realisation of Smart Non-prehensile Manipulation Strategies for Robots
  • Automatic Formative Assessment for Students’ Short Text Answers through Feature Extraction
  • Intelligent Neural Network Design for Robotic Embedded Vision
  • Automatic Question and Answer Generation from Domain-Specific Text for Exams
  • Improving Accessibility and Transparency of Large-Scale Robot Experience Data using a Natural Language Interface
  • Visuomotor Policy Learning using Dense Descriptors for Robot Manipulation
  • Enhancing Model Predictive Control to Improve the Navigation of a Quasi Omni-Directional Mobile Robot
  • Vision-based safe robot motion for human-robot collaboration
  • Image-based object detection for autonomous parking using convolutional neural networks
  • Identifying object grasps for manipulation
  • Deep Reinforcement Learning for Continuous Control Docking of Autonomous Underwater Vehicles: A Benchmarking Study
  • Efficient architectures for object pose estimation
  • Improving Uncertainty Estimates in Deep Learning Models using Knowledge Distillation

Master Thesis Defense 2020 

  • PillarFPN: A Feature Pyramid Extension to PointPillars for 3D Object Detection.
  • Knowledge-Enabled Specification of Composable Robot Motion Control Architectures
  • Efficient and Context-aware Pedestrian Trajectory Prediction
  • An investigation of regression as an avenue to find precision-runtime trade-off for object segmentation.
  • Evaluating Uncertainty Estimation Methods on 3D Semantic Segmentation of Point Clouds
  • Development of a New Quality Prediction Approach and Aggregation of a Quality Prediction Pipeline
  • Multi-Robot Task Allocation with Temporal Constraints and Uncertain Durations
  • Feature Extraction for Time Series Classification
  • Generative machine learning model obfuscation
  • Compositional Machine Learning Models for Robotic Manipulation Behaviors
  • Estimating Confidence in Spatio-Temporal Models
  • Explainable Assistive Short Answer Grading
  • A Comprehensive Evaluation of Uncertainty Quantification Methods in Deep Learning
  • Black-Box Optimization of Object Detector Hyper-Parameters.
  • Compliant Manipulation with Reinforcement Learning Guided by Task Specification
  • Skeleton Based Action Recognition: Enhancing Co-occurrence Explorer with View Adaptive Network
  • Lazy Robot Control by Relaxation of Motion and Force Constraints
  • Immersive Telepresence Through 360° Video Streaming: Potentials and Limitations Today
  • Evaluation of Deep Learning Technique for Impulse Sound Classification in 2D Representation
  • Comparative Evaluation of Image Data Selection Methods for Human Pose Estimation

Master Thesis Defense 2019 

  • Vision Based Human Fall Detection
  • Automated gait and pose analysis for lameness detection in cows
  • Realtime Deep Learning for Multispectral Human Detection
  • Multiagent System for Warehouse Material Flow Control
  • Poin cloud classification of real objects using CNNs
  • Semantic localization and navigation for indoor robots using OpenStreetMap
  • A mediator system for querying heterogeneous data in robotic applications​
  • An Evaluation of Deep Learning Object Detection Pipelines for Maritime Application Purposes

Links

Further links

R&D Project Defense