Fred Godtliebsen,
Eirik Myrvoll-Nilsen,
Lasse Holmstr枚m
:
Comments on: Data integration via analysis of subspaces (DIVAS)
Test - An Official Journal of the Spanish Society of Statistics and Operations Research 2024 /
Iver Martinsen,
David Wade,
Benjamin Ricaud,
Fred Godtliebsen
:
The 3-billion fossil question: How to automate classification of microfossils
Artificial Intelligence in Geosciences 2024 /
Marit Dagny Kristine Jenssen,
Elisa Salvi,
Egil Andreas Fors,
Ole Andreas Nilsen,
Phuong Dinh Ngo,
Miguel Angel Tejedor Hernandez
m.fl.:
Exploring Pain Reduction through Physical Activity: A Case Study of Seven Fibromyalgia Patients
Bioengineering 2024 /
Tejedor H Miguel Angel,
Sigurd Hjerde,
Jonas Nordhaug Myhre,
Fred Godtliebsen
:
Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes
Diagnostics (Basel) 07. oktober 2023 /
Jonathan E Berezowski,
Thomas Andre Haugland Johansen,
Jonas Nordhaug Myhre,
Fred Godtliebsen
:
Variable Depth Bayesian Neural Networks Using Reversible Jumps
IEEE conference proceedings 2022 /
Taridzo Fred Chomutare,
Miguel Angel Tejedor Hernandez,
Therese Olsen Svenning,
Luis Marco Ruiz,
Maryam Tayefi Nasrabadi,
Karianne Fredenfeldt Lind
m.fl.:
Artificial Intelligence Implementation in Healthcare: A Theory-Based Scoping Review of Barriers and Facilitators
International Journal of Environmental Research and Public Health (IJERPH) 2022 /
Isak Paasche Edvardsen,
Anna Teterina,
Thomas Haugland Johansen,
Jonas Nordhaug Myhre,
Fred Godtliebsen,
Napat Limchaichana Bolstad
:
Automatic detection of the mental foramen for estimating mandibular cortical width in dental panoramic radiographs: the seventh survey of the Troms酶 Study (Troms酶7) in 2015-2016
Journal of International Medical Research 22. november 2022 /
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
Applied Sciences 2022 / /
Maryam Tayefi,
Phuong Ngo,
Taridzo Chomutare,
Hercules Dalianis,
Elisa Salvi,
Andrius Budrionis
m.fl.:
Challenges and opportunities beyond structured data in analysis of electronic health records
Wiley Interdisciplinary Reviews: Computational Statistics 14. februar 2021 /
Thomas Haugland Johansen,
Steffen Aagaard S酶rensen,
Kajsa M酶llersen,
Fred Godtliebsen
:
Instance Segmentation of Microscopic Foraminifera
Applied Sciences 2021 /
Marit Dagny Kristine Jenssen,
Per Atle Bakkevoll,
Phuong Ngo,
Andrius Budrionis,
Asbj酶rn Johansen Fagerlund,
Maryam Tayefi
m.fl.:
Machine Learning in Chronic Pain Research: A Scoping Review
Applied Sciences 2021 /
Stig Uteng,
Eduardo Quevedo,
Gustavo M. Callico,
Irene Casta帽o,
Gregorio Carretero,
Pablo Almeida
m.fl.:
Curve-Based Classification Approach for Hyperspectral Dermatologic Data Processing
Sensors 2021 /
Stig Uteng,
Thomas Haugland Johansen,
Jose Ignacio Zaballos,
Samuel Ortega,
Lasse Holmstr枚m,
Gustavo M. Callico
m.fl.:
Early Detection of Change by Applying Scale-Space Methodology to Hyperspectral Images
Applied Sciences 2020 /
Miguel Angel Tejedor Hernandez,
Ashenafi Zebene Woldaregay,
Fred Godtliebsen
:
Reinforcement learning application in diabetes blood glucose control: A systematic review
Artificial Intelligence in Medicine 2020 /
Phuong Ngo,
Miguel Angel Tejedor Hernandez,
Maryam Tayefi,
Taridzo Chomutare,
Fred Godtliebsen
:
Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities
Applied Sciences 2020 /
Kajsa M酶llersen,
Jon Yngve Hardeberg,
Fred Godtliebsen
:
A probabilistic bag-to-class approach to multiple-instance learning
Data 26. juni 2020 /
Taridzo Chomutare,
Kassaye Yitbarek Yigzaw,
Andrius Budrionis,
Alexandra Makhlysheva,
Fred Godtliebsen,
Hercules Dalianis
:
De-identifying Swedish EHR text using public resources in the general domain
Studies in Health Technology and Informatics 2020 /
Sebastian Andres Acu帽a Maldonado,
Ida Sundvor Opstad,
Fred Godtliebsen,
Balpreet Singh Ahluwalia,
Krishna Agarwal
:
Soft thresholding schemes for multiple signal classification algorithm
Optics Express 2020 /
Samuel Ortega,
Martin Halicek,
Himar Fabelo,
Rafael Camacho,
Maria de La Luz Plaza,
Fred Godtliebsen
m.fl.:
Hyperspectral imaging for the detection of glioblastoma tumor cells in H&E slides using convolution neural networks
Sensors 30. mars 2020 /
Samuel Ortega,
Martin Halicek,
Himar Fabelo,
Raul Guerra,
Carlos Lopez,
Marylene Lejaune
m.fl.:
Hyperspectral imaging and deep learning for the detection of breast cancer cells in digitized histological images
Proceedings of SPIE, the International Society for Optical Engineering 2020 /
Giovanni Sebastiani,
Stig Uteng,
Fred Godtliebsen,
Jan Pol脿k,
Jan Bro啪
:
Estimation of Blood Glucose Concentration During Endurance Sports
International Journal of Biology and Biomedical Engineering 2020 /
Jonas Nordhaug Myhre,
Miguel Angel Tejedor Hernandez,
Ilkka Kalervo Launonen,
Anas El Fathi,
Fred Godtliebsen
:
In-silico evaluation of glucose regulation using policy gradient reinforcement learning for patients with type 1 diabetes mellitus
Applied Sciences 11. september 2020 /
Kristian Hindberg,
Jan Hannig,
Fred Godtliebsen
:
A novel scale-space approach for multinormality testing and the k-sample problem in the high dimension low sample size scenario
PLOS ONE 2019 /
Thomas Haugland Johansen,
Kajsa M酶llersen,
Samuel Ortega,
Himar Fabelo,
Aday Garcia,
Gustavo Callico
m.fl.:
Recent advances in hyperspectral imaging for melanoma detection
Wiley Interdisciplinary Reviews: Computational Statistics 2019 /
John S. Hammond,
Fred Godtliebsen,
Sonja Eriksson Steigen,
I. Neil Guha,
Judy Wyatt,
Arthur Revhaug
m.fl.:
The effects of terlipressin and direct portacaval shunting on liver hemodynamics following 80% hepatectomy in the pig
Clinical Science 2019 /
Phuong Ngo,
Maryam Tayefi,
Anne Torill Nordsletta,
Fred Godtliebsen
:
Food recommendation using machine learning for physical activities in patients with type 1 diabetes
Link枚ping Electronic Conference Proceedings 2019 /
David Wade,
Fred Godtliebsen,
Benjamin Ricaud,
Iver Martinsen
:
A deep learning pipeline for automatic microfossil analysis and classification
2024
Iver Martinsen,
David Wade,
Benjamin Ricaud,
Fred Godtliebsen
:
A deep learning pipeline for automatic microfossil analysis and classification
2024
Iver Martinsen,
Fred Godtliebsen,
Steffen Aagaard S酶rensen,
Eirik Myrvoll-Nilsen,
Samuel Ortega Sarmiento,
Miguel Angel Tejedor Hernandez
:
Are humans an AI uncertain about the same things?
2024
Iver Martinsen,
Fred Godtliebsen,
Benjamin Ricaud,
David Wade
:
The 3-billion fossil question
2024
Steffen Aagaard S酶rensen,
Eirik Myrvoll-Nilsen,
Iver Martinsen,
Fred Godtliebsen,
Stamatia Galata,
Juho Junttila
m.fl.:
Detection and identification of environmental faunal proxies in digital images and video footage from northern Norwegian fjords and coastal waters using deep learning object detection algorithms
2024
Iver Martinsen,
Benjamin Ricaud,
David Wade,
Fred Godtliebsen
:
Grouping microscopic fossils without labels using self-supervision
2023
Fred Godtliebsen
:
Sparse networks in deep learning
2023
Fred Godtliebsen
:
Trans-dimensional Bayesian Deep Learning
2023
Fred Godtliebsen
:
Sparse Networks in Deep Learning
2023
Eirik Myrvoll-Nilsen,
Steffen Aagaard-S酶rensen,
Stamatia Galata,
Thomas Haugland Johansen,
Iver Martinsen,
Morten Hald
m.fl.:
Automated classification of microscopic foraminifera
2023
Eirik Myrvoll-Nilsen,
Steffen Aagaard-S酶rensen,
Stamatia Galata,
Thomas Haugland Johansen,
Iver Martinsen,
Morten Hald
m.fl.:
Automating object detection and classification of foraminifera
2023
Iver Martinsen,
Benjamin Ricaud,
David Wade,
Fred Godtliebsen
:
An efficient pipeline for microfossil analysis
2023
Steffen Aagaard S酶rensen,
Eirik Myrvoll-Nilsen,
Stamatia Galata,
Thomas Haugland Johansen,
Iver Martinsen,
Morten Hald
m.fl.:
Automated image/video classification and object detection of foraminifera
2023
Fred Godtliebsen,
Steffen Aagaard S酶rensen,
Morten Hald
:
Automatisk overv氓kning av havbunnen
David Wade,
Iver Martinsen,
Erik Anthonissen,
Alex Cullum,
Robert Williams,
Fred Godtliebsen
m.fl.:
Species Classification Automation for Microfossil Photomicrograph Images
2022
Iver Martinsen,
David Wade,
Fred Godtliebsen,
Benjamin Ricaud
:
SCAMPI - Species Classification Automation for Microfossil Photomicrograph Images
2022
Phuong Ngo,
Eirik 脜rsand,
Fred Godtliebsen
:
Toward A Personalized Decision Support System for Blood Glucose Management During and After Physical Activities in Patients with Type 1 Diabetes
Diabetes Technology & Therapeutics 2020
Thomas Haugland Johansen,
Kajsa M酶llersen,
Samuel Ortega,
Himar Fabelo,
Gustavo Callico,
Fred Godtliebsen
:
Detecting skin cancer using hyperspectral images
Advanced Science News 2020
Beatriz Martinez-Vega,
Eduardo Quevedo,
Raquel Leon,
Himar Fabelo,
Samuel Ortega,
Gustavo M. Callico
m.fl.:
Statistics-based Classification Approach for Hyperspectral Dermatologic Data Processing
2020
Jonas Nordhaug Myhre,
Miguel Angel Tejedor Hernandez,
Ilkka Kalervo Launonen,
Fred Godtliebsen
:
In-silico Evaluation of Trust Region Policy Optimization Reinforcement Learning for T1DM Closed-Loop Control
2019
Sebastian Andres Acu帽a Maldonado,
G M A Mehedi Hussain,
Fred Godtliebsen,
Balpreet Singh Ahluwalia,
Hoai Phuong Ha,
Dilip K. Prasad
m.fl.:
Multiple Signal Classiflcation: Challenges on the Route from
Millimeter Resolution to Nanometer Resolution
2019
Jonas Nordhaug Myhre,
Miguel Angel Tejedor Hernandez,
Ilkka Kalervo Launonen,
Fred Godtliebsen
:
In-silico Evaluation of Type-1 Diabetes Closed-Loop Control using Deep Reinforcement Learning
2019
Phuong D. Ngo,
Fred Godtliebsen
:
Data-Driven Robust Control Using Reinforcement Learning
2018
Phuong D. Ngo,
Miguel Angel Tejedor Hernandez,
Fred Godtliebsen
:
A Decision Support Tool for Optimal Control of Planet Temperature Using Reinforcement Learning
2018