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- 2020
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Mark
Blood Cell Data Augmentation using Deep Learning Methods
(2020) In Master's Theses in Mathematical Sciences FMAM05 20192
Mathematics (Faculty of Engineering)- Master (Two yrs)
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Mark
Adaptive Reference Images for Blood Cells using Variational Autoencoders and Self-Organizing Maps
(2020) In Master's Theses in Mathematical Sciences FMAM05 20201
Mathematics (Faculty of Engineering)- Master (Two yrs)
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Mark
Semi-Supervised Medical Image Segmentation with Equivariance Regularization
(2020) In Master’s Theses in Mathematical Sciences FMAM05 20192
Mathematics (Faculty of Engineering)- Master (Two yrs)
-
Mark
Analysing pedestrian movement with the Flowity software
- Bach. Degree
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Mark
Using Opaque AI for Smart Grids
- Bach. Degree
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Mark
Deep Learning Approach to Material Properties
- Bach. Degree
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Mark
Automated bone segmentation in computed tomography using deep learning with distance maps
(2020) In Master's Theses in Mathematical Sciences FMAM05 20201
Mathematics (Faculty of Engineering)- Master (Two yrs)
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Mark
Detecting Deepfakes and Forged Videos Using Deep Learning
(2020) In Master's Theses in Mathematical Sciences FMAM05 20201
Mathematics (Faculty of Engineering)- Master (Two yrs)
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Mark
Cost-Optimized Event Detection in Football Video
(2020) In Master's Theses in Mathematical Sciences FMAM05 20201
Mathematics (Faculty of Engineering)- Master (Two yrs)
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Mark
Investigating the Use of Machine Learning to Detect Unilateral Arm Weakness
(2020) In Master's Theses in Mathematical Sciences FMAM05 20201
Mathematics (Faculty of Engineering)- Master (Two yrs)