Line Harder Clemmensen

Orcid: 0000-0001-5527-5798

According to our database1, Line Harder Clemmensen authored at least 47 papers between 2007 and 2024.

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Bibliography

2024
Evaluation of Large Language Models: STEM education and Gender Stereotypes.
CoRR, 2024

Classification of Tennis Actions Using Deep Learning.
CoRR, 2024

Beyond Accuracy: Fairness, Scalability, and Uncertainty Considerations in Facial Emotion Recognition.
Proceedings of the Northern Lights Deep Learning Conference, 2024

A Self-Organizing Clustering System for Unsupervised Distribution Shift Detection.
Proceedings of the International Joint Conference on Neural Networks, 2024

Fair Soft Clustering.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Pantypes: Diverse Representatives for Self-Explainable Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Proximal methods for sparse optimal scoring and discriminant analysis.
Adv. Data Anal. Classif., December, 2023

On Crowdsourcing-Design with Comparison Category Rating for Evaluating Speech Enhancement Algorithms.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Interpretability by design using computer vision for behavioral sensing in child and adolescent psychiatry.
CoRR, 2022

Computational behavior recognition in child and adolescent psychiatry: A statistical and machine learning analysis plan.
CoRR, 2022

Speech Detection For Child-Clinician Conversations In Danish For Low-Resource In-The-Wild Conditions: A Case Study.
CoRR, 2022

Data Representativity for Machine Learning and AI Systems.
CoRR, 2022

Compressing CNN Kernels for Videos Using Tucker Decompositions: Towards Lightweight CNN Applications.
Proceedings of the 2022 Northern Lights Deep Learning Workshop, 2022

Continuous Metric Learning For Transferable Speech Emotion Recognition and Embedding Across Low-resource Languages.
Proceedings of the 2022 Northern Lights Deep Learning Workshop, 2022

Towards Transferable Speech Emotion Representation: On Loss Functions for Cross-Lingual Latent Representations.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Unsupervised Spectral Unmixing For Telluric Correction Using A Neural Network Autoencoder.
CoRR, 2021

Sampling To Improve Predictions For Underrepresented Observations In Imbalanced Data.
CoRR, 2021

Towards Interpretable and Transferable Speech Emotion Recognition: Latent Representation Based Analysis of Features, Methods and Corpora.
CoRR, 2021

Consistent and accurate estimation of stellar parameters from HARPS-N Spectroscopy using Deep Learning.
Proceedings of the 2021 Northern Lights Deep Learning Workshop, 2021

2020
A generalized linear joint trained framework for semi-supervised leaning of sparse features.
CoRR, 2020

Weight Sharing and Deep Learning for Spectral Data.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Deep learning for Chemometric and non-translational data.
CoRR, 2019

2018
Computer Aided Identification of Motion Disturbances Related to Parkinson's Disease.
Proceedings of the PRedictive Intelligence in MEdicine - First International Workshop, 2018

2017
Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection.
Eng. Appl. Artif. Intell., 2017

2016
Regularized generalized eigen-decomposition with applications to sparse supervised feature extraction and sparse discriminant analysis.
Pattern Recognit., 2016

Forest Floor Visualizations of Random Forests.
CoRR, 2016

2015
Pig herd monitoring and undesirable tripping and stepping prevention.
Comput. Electron. Agric., 2015

Characterizing Digital Light Processing (DLP) 3D Printed Primitives.
Proceedings of the Image Analysis - 19th Scandinavian Conference, 2015

Non-negative Matrix Factorization for Binary Data.
Proceedings of the KDIR 2015, 2015

2014
On Weighted Support Vector Regression.
Qual. Reliab. Eng. Int., 2014

Hyperspectral imaging based on diffused laser light for prediction of astaxanthin coating concentration.
Mach. Vis. Appl., 2014

Supervised feature selection for linear and non-linear regression of L<sup>⁎</sup>a<sup>⁎</sup>b<sup>⁎</sup> color from multispectral images of meat.
Eng. Appl. Artif. Intell., 2014

Sparse and shrunken estimates of MRI networks in the brain and their influence on network properties.
Proceedings of the Medical Imaging 2014: Image Processing, 2014

How do Student Evaluations of Courses and of Instructors Relate?.
Proceedings of the CSEDU 2014, 2014

2013
Statistical Quality Assessment of Pre-fried Carrots Using Multispectral Imaging.
Proceedings of the Image Analysis, 18th Scandinavian Conference, 2013

Correlation of iris biometrics and DNA.
Proceedings of the 1st International Workshop on Biometrics and Forensics, 2013

DCT-based characterization of milk products using diffuse reflectance images.
Proceedings of the 18th International Conference on Digital Signal Processing, 2013

Text Mining in Students' Course Evaluations - Relationships between Open-ended Comments and Quantitative Scores.
Proceedings of the CSEDU 2013, 2013

Effects of Mid-term Student Evaluations of Teaching as Measured by End-of-Term Evaluations - An Emperical Study of Course Evaluations.
Proceedings of the CSEDU 2013, 2013

2012
Effects of network resolution on topological properties of human neocortex.
NeuroImage, 2012

Data Driven Constraints for the SVM.
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012

2011
Sparse Discriminant Analysis.
Technometrics, 2011

2010
A comparison of dimension reduction methods with application to multi-spectral images of sand used in concrete.
Mach. Vis. Appl., 2010

NetRaVE: constructing dependency networks using sparse linear regression.
Bioinform., 2010

2009
Temporal reflectance changes in vegetables.
Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

2007
Precise acquisition and unsupervised segmentation of multi-spectral images.
Comput. Vis. Image Underst., 2007

Individual Discriminative Face Recognition Models Based on Subsets of Features.
Proceedings of the Image Analysis, 15th Scandinavian Conference, 2007


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