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- 2024
-
Mark
Virtual H&E Staining Using PLS Microscopy and Neural Networks
(
- Master (Two yrs)
- 2023
-
Mark
An Open-Source Autoencoder Compression Tool for High Energy Physics
(
- Master (One yr)
- 2022
-
Mark
Evolutionary Properties of Neural Networks: Exploration of Robustness and Evolvability in the Genotype-Phenotype Map
(
- Master (Two yrs)
-
Mark
Investigating Machine Learning for verification of AMBA APB protocol.
(
- Master (Two yrs)
-
Mark
Improving a Background Model for Tracking and Classification of Objects in LiDAR 3D Point Clouds
(
- Master (Two yrs)
-
Mark
Identifying Piggybacking with Radar and Neural Networks
(
- Master (Two yrs)
-
Mark
Biologically informed neural network for subphenotype classification in septic AKI
(
- Master (Two yrs)
- 2021
-
Mark
Image Classification using Functional Analysis and Neural Networks
(
- Master (One yr)
-
Mark
Investigation of dynamic control ML algorithms on existing and future Arm microNPU systems
(
- Master (Two yrs)
-
Mark
Keystroke Classification of Motion Sensor Data - An LSTM Approach
(
- Master (Two yrs)
-
Mark
AI-based Classification of Radar Signals
(
- Master (Two yrs)
- 2020
-
Mark
Machine learning methods on Swedish geological data
(
- Master (Two yrs)
-
Mark
Implementation of a Deep Learning Inference Accelerator on the FPGA.
(
- Master (Two yrs)
-
Mark
Adaptive Reference Images for Blood Cells using Variational Autoencoders and Self-Organizing Maps
(
- Master (Two yrs)
-
Mark
JPEG-deblocking of Blood Cell Images using Deep Learning
(
- Master (Two yrs)
-
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
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)
-
Mark
Energy reconstruction with artificial neural networks on LDMX simulations
(
- Bach. Degree
- 2019
-
Mark
User Equipment Characterization using Machine Learning
(
- Master (Two yrs)
-
Mark
Memory Efficient Semantic Segmentation for Embedded Systems
(
- Master (Two yrs)
-
Mark
Forecasting the USD/SEK exchange rate using deep neural networks
(
- Bach. Degree
-
Mark
Exploring the LASSO as a Pruning Method
(
- Bach. Degree
- 2018
-
Mark
Vehicle Counting using Video Metadata
(
- Prof. qual. >4 yrs
-
Mark
An investigation of Recent Deep Learning Techniques Applied to Blood Cell Image Analysis
(
- Master (Two yrs)
-
Mark
Steering Angle Prediction by a Deep Neural Network and its Domain Adaption Ability
(
- Master (Two yrs)
-
Mark
Neural Networks and the Stock Market
(
- Bach. Degree
-
Mark
sEMG Classication with Convolutional Neural Networks: A Multi-Label Approach for Prosthetic Hand Control
(
- Master (Two yrs)
-
Mark
An exploration of the current state-of-the-art in automatic music transcription - with proposed improvements using machine learning
(
- Master (Two yrs)
- 2016
-
Mark
Distributing a Neural Network on Axis Cameras
(
- Prof. qual. >4 yrs
-
Mark
Face Recognition Based on Embedded Systems
(
- Master (Two yrs)
-
Mark
Classification in Bone Scintigraphy Images Using Convolutional Neural Networks
(
- Master (Two yrs)
- 2015
-
Mark
MAIA: The role of innate behaviors when picking flowers in Minecraft with Q-learning
(
- Master (Two yrs)
- 2013
-
Mark
Careem: A car within 15 minutes
(
- Univ. Diploma
- 2011
-
Mark
The Double Feedback Model of Neural Control of Locomotion: Is Immature Behavior Needed to Develop Mature Behavior?
(
- Master (Two yrs)
- 2007
-
Mark
Managing Credit Risk: Assessing the Probability of Corporate Bankruptcy using Quantitative Risk Analysis
(
- Master (One yr)