Data Management & Biometrics (DMB)

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Open Bachelor Assignments

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

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[D] A probabilistic approach towards handling data quality problems and imperfect data integration tasks

[M] Adversarial noise in convolutional deep networks

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

[M] Building energy prediction using Artificial Intelligence methods

[M] Deep learning models for point cloud classification/semantic segmentation.

[M] Efficient Learning in Deep Learning through Neuroscience theories.

[M] Explaining Cyclists Activities Through Multidimensional Projections.

[M][B] Fourier-basis noise data augmentation

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

[D][B] Exploring approximate string matching methods on time series data

[D][B] Assess the effect of sample size rescaling in selective sweep detection

[M] A framework for ethical AI

[B] Finishing and improving of finger vein system

[M] Machine Learning for Model-based Diagnosis of Cyberphysical Systems

[M] Making Bayesian Networks Available for Clinical Decision Support

[B] Morphing detection based on analysis of local spectrum

[B] Morphing detection based on facial marks

[B] Morphing robust face recognition

[D] Process Mining for Logistics Applications

[D] Process Mining Software Logs

[B][M] Recognising and understanding human activities from videos

[M] Scalable Deep Learning

[D] Subpopulation process mining based on graph matching

[D] Subpopulation Process Mining in Health

[B] SQUEEZE: a hybrid cloud-edge implementation

[D][M] Synthetic data production and privacy evaluation for Hospital Information System(HIS)

[D] Tracing data utility for noise adding plugins in process mining

[M] Unsupervised learning using NLP for recommendation clustering

[B] [M] Visual Semantic Role Labelling

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