Data Management & Biometrics (DMB)

UTFaculteitenEEMCSDisciplines & departementenDMBAssignmentsOpen AssignmentsOpen Master Assignments

Open Master Assignments

D = Data engineering, M = Machine learning, B = Biometrics & computer vision

[MB] Will it fail? Generating videos of actions fails

[M] Virtual symphony: matching off-tempo audio from different instruments

[M] Uni-modal to multi-modal model merging

[MB] Deriving text descriptions from visual model's predictions

[B] Heritage Biometrics – Possibilities with AI in Furniture & Wood Conservation

[B] Heritage Biometrics: does every painter paint himself?

[B] Heritage biometrics – 3D acquisition design for fingerprints, scratches and toolmarks on works of art

[B] Heritage biometrics – artist profiling from 3D fingerprints

[M] BBI Process Mining: Predict the remaining processing time of a pallet for an automated refrigerated warehouse

[M] Machine learning to quantify e3value business models

[D] Analysing coaching and therapy reports with Natural Language Processing/LLMs (Dutch, CS&BIT)

[M] Research into the AI-Revolution in Camera Technology at LOOGISCH

[M] Process Mining Pancreascarcinoom

[M] Event-streaming Algorithm for Self-adaptive Distributed Vehicle Route Guidance in Urban Networks

[M] Comparing attack graphs with business process models for modeling attacker strategies

[M] Optimisation of Complication Registration with Text Mining and Machine Learning

[M] LegalTech: AI and Legal processes

[M] Advancing Healthcare Process Simulation: Automating Discrete Event Models from Process Data

[M] Algorithm Development for Analysis of Heart Tissue

[B] Temporal Surgical Video Segmentation for Medical Dataset Curation

[B] Surgical Phase Pattern Recognition from Video Data

[B] Driver Behavior Understanding for Monitoring Fatigue and Anomalous Behavior in Autonomous Driving

[M] Fitness prediction for hip surgery for elderly patients

[D] Text mining to retrieve suspected cause of acute kidney injury from medical files

[M] Probability prediction for acute kidney injury

[M] (Multimodal) Admission prediction for patients in the cardiac emergency department

[M] Fast-track outcome prediction

[M] Real-time medication monitoring for patients with chronic pulmonary conditions

[D] Lesion detection model to monitor MS progression in brain MRI scans

[M] Quality Control on radiology MR reports

[M] NLP model to predict diabetes type and year of diagnosis from medical texts

[B] Discovery of missing objects in predefined scene images

[B] Pose Estimation in Handball Videos for Personalized Training

[B] Egocentric vision for human behaviour understanding

[B] Understanding the Effect of Image Quality and Resolution on Skin Lesion Recognition

[B] Recognition of Crops Relevant for Food Security from Images – Dataset Compilation and Classification Framework Design

[M] Artificial Intelligence against Cancer

[M] AERIAL IMAGE SEGMENTATION WITH DATA-EFFICIENT ADAPTATION OF FOUNDATION MODELS

[B] Benchmarking Medical Class-OOD (aka Open Set Recognition) Detection

[B] OOD detection on MediCLIP

[B] Can Normalizing Disentangled Flows Detect OOD data?

[B] Medical OOD detection with an Exponentially Tilted Gaussian Prior for beta-Variational Autoencoders

[B] Can you find the Gorilla in the CT scan? (2 topics: Sample and Object level)

[B] Why can’t Vision-Language Models like CLIP find OOD data in medical images? Or can they? How?

[B] Can Normalizing Disentangled Flows Detect OOD data?

[B] Disentangled Flows for Face editing

[B] Disentangled Flows for Anomaly Detection

Lifestyle Data Futures

[B] Self-Supervised Out-of-Distribution Detection

[B] Unsupervised Anomaly Detection Under Domain Shifts

[B] [M] AUTO: Auto encoders in face recognition

[M] Auto Data Evaluation using Machine Learning @ROSEN Enschede

[M] Object Detection for Water Pipeline Inspection @ROSEN Enschede

[M] Autoncoders and Recovering High Frequency Components

[D][M] BIO marker-based COVID Severity prediction and data quality exploration

[M] [B] Computer Vision & Machine Learning @ Lely

[M] Decoding EMG using A Riemannian Geometry approach

[M] Decoding EMG using Autoencoders

[B] [M] DIET: from obese data to sparse face models

[M] Explainable Machine Learning

[M] Explaining Estrus Classifications

[B] [M] FISWG AUTO: Automatic extraction and use of forensic facial features

[M] Large-scale data mining & NLP @ OCLC - Leiden, NL

[M] Machine Learning

[M] Machine Learning and Natural Language Processing Internship @Nedap

[B] Morphing robust face recognition

[B] Evaluation of AI-driven interpretation on microscopic images in oncology

[M] Deep learning in medical imaging project in Berlin using 3D-printed phantom

[M][B] Digital media - using neural networks for steganography

[M][B] Visual place recognition

[M][B] Fourier-basis noise image data augmentation for CNN robustness

[M][B] Deblurring and disentangled representations of cell images via deep learning

[M] Detect and correct wrong transliterations

[M][B] Deep learning techniques for deblurring cell images utilizing geometry

[M] How do different down-sampling methods affect neural networks’ reaction towards different frequencies?

[M] Motion magnification for engineered heart tissue microscopy videos

[M] Learning temporally-extended state and action representations in Deep Reinforcement Learning

[M] Automated Algorithm Configuration of Sparse Neural Networks

[M] Mortality prediction after hip fracture surgery. Could Machine Learning add value?

[D] Natural Language Processing for diagnosis of patients with unexplainable Left Ventricle Hypertrofia

[M] Point Cloud Classification using Context based Feature Engineering

[D] Process Mining Opportunities at Univé

[M] Project: E-Manager Chronic Diseases

[M] Semi-Supervised Deep Learning for Point Cloud Classification

[M] Serendipity at the MuseumFabriek

[B] TURBULENCE: 2D gen – 3D pose pipeline – atmospheric turbulence

[M] Using physiological signals to monitor mental state of Cybersecurity experts at Dutch Bank

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