Ulf Geir Indahl

Norwegian University of Life Sciences — Norway

Chemistry · Physical Sciences

28h-index2.1kcitations78works7.52yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Spectroscopy and Chemometric Analyses(29), Advanced Chemical Sensor Technologies(8), Radiomics and Machine Learning in Medical Imaging(8), Gene expression and cancer classification(7), Sensory Analysis and Statistical Methods(7)

Publications78 total

Using Density and Fuzzy Clustering for Data Cleaning and Segmental Description of Livestock Data
Journal of Agricultural Biological and Environmental Statistics·2024· 2 citedOpen Access
A New Formula for Faster Computation of the K-Fold Cross-Validation and Good Regularisation Parameter Values in Ridge Regression
IEEE Access·2024· 13 citedOpen Access
Tsetlin Machine in DNA sequence classification : Application to prokaryote gene prediction / A match made in silico
2023· 1 cited
Selection of principal variables through a modified Gram–Schmidt process with and without supervision
Journal of Chemometrics·2023· 5 citedOpen Access
Extraction of photoluminescence with Pearson correlation coefficient from images of field-installed photovoltaic modules
Journal of Applied Physics·2023· 9 cited
Non-linear shrinking of linear model errors
Analytica Chimica Acta·2023· 7 citedOpen Access
A New Formula for Faster Computation of the K-Fold Cross-Validation and Good Regularisation Parameter Values in Ridge Regression
arXiv (Cornell University)·2022Open Access
Swiss knife covariates selection: A unified algorithm for covariates selection in single block, multiblock, multiway, multiway multiblock cases including multiple responses
Journal of Chemometrics·2022· 2 citedOpen Access
Author response for "SWISS KNIFE COVARIATES SELECTION (SKCOVSEL) : A UNIFIED ALGORITHM FOR COVARIATES SELECTION IN SINGLE BLOCK, MULTIBLOCK, MULTIWAY, MULTIWAY MULTIBLOCK CASES INCLUDING MULTIPLE RESPONSES"
2022
The canonical partial least squares approach to analysing multiway datasets—N‐CPLS
Journal of Chemometrics·2022· 7 citedOpen Access
Author response for "THE CANONICAL PARTIAL LEAST SQUARES APPROACH TO ANALYSING MULTIWAY DATASETS – N‐CPLS"
2022
On the possible benefits of deep learning for spectral preprocessing
Journal of Chemometrics·2021· 47 citedOpen Access
Author response for "On the possible benefits of deep learning for spectral preprocessing"
2021Open Access
A comparison of methods for fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers
Physics in Medicine and Biology·2021· 47 cited
RENT—Repeated Elastic Net Technique for Feature Selection
IEEE Access·2021· 29 citedOpen Access
Much faster cross‐validation in PLSR‐modelling by avoiding redundant calculations
Journal of Chemometrics·2020· 11 citedOpen Access
SAnE: Smart Annotation and Evaluation Tools for Point Cloud Data
IEEE Access·2020· 27 citedOpen Access
Orders of magnitude speed increase in partial least squares feature selection with new simple indexing technique for very tall data sets
Journal of Chemometrics·2019· 6 cited
Deep learning for automatic tumour segmentation in PET/CT images of patients with head and neck cancers
arXiv (Cornell University)·2019· 29 citedOpen Access
Addressing overfitting on point cloud classification using Atrous XCRF
ISPRS Journal of Photogrammetry and Remote Sensing·2019· 43 citedOpen Access
page 1 of 4Next →

Frequent Co-authors

Kristian Hovde Liland(13), Tormod Næs(9), Cecilia Marie Futsæther(6), Harald Martens(5), Oliver Tomić(5), Håvard Tveite(5), Eirik Malinen(4), Knut Kvaal(4), Stig W. Omholt(4), Hasan Asyari Arief(4), Joakim Skogholt(4), Turid Torheim(3), Kjell Heuser(3), Erlend A. Nagelhus(3), Paul R. Berg(3), Sigbjørn Lien(3), Ole Petter Ottersen(3), Kristin Tøndel(3), Heidi Lyng(2), Erik Taubøll(2)