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- 2021
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Mark
Keystroke Classification of Motion Sensor Data - An LSTM Approach
(
- Master (Two yrs)
- 2020
-
Mark
Implementation of a Deep Learning Inference Accelerator on the FPGA.
(
- Master (Two yrs)
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Mark
Adaptive Reference Images for Blood Cells using Variational Autoencoders and Self-Organizing Maps
(
- Master (Two yrs)
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Mark
Energy reconstruction with artificial neural networks on LDMX simulations
(
- Bach. Degree
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Mark
Using X-band Radar with a Neural Network to Forecast Combined Sewer Flow - A case study in Lund
(
- Master (Two yrs)
-
Mark
Detecting Deepfakes and Forged Videos Using Deep Learning
(
- Master (Two yrs)
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Mark
Exploring the application of neural networks in predictions of nuclear binding energies
(
- Bach. Degree
-
Mark
A Study of Time-Stepping Methods for Optimization in Supervised Learning
2020) In Master's Theses in Mathematical Sciences NUMM11 20201(
Mathematics (Faculty of Engineering)
Centre for Mathematical Sciences- Master (Two yrs)
-
Mark
Machine learning methods on Swedish geological data
(
- Master (Two yrs)
-
Mark
JPEG-deblocking of Blood Cell Images using Deep Learning
(
- Master (Two yrs)