Michael Kampffmeyer
Førsteamanuensis / Maskinlæring
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Christian Kampffmeyer
:
Leveraging tensor kernels to reduce objective function mismatch in deep clustering
Pattern Recognition 2024 DOI
Duy Khoi Tran,
van Nhan Nguyen,
Davide Roverso,
Robert Jenssen,
Michael Christian Kampffmeyer
:
LSNetv2: Improving weakly supervised power line detection with bipartite matching
Expert Systems With Applications 2024 DOI
Samuel Kuttner,
Luigi Tommaso Luppino,
Laurence Convert,
Otman Sarrhini,
Roger Lecomte,
Michael Christian Kampffmeyer
m.fl.:
Deep learning derived input function in dynamic [18F]FDG PET imaging of mice
Frontiers in Nuclear Medicine 2024 DOI
Changkyu Choi,
Michael Kampffmeyer,
Nils Olav Handegard,
Arnt-Børre Salberg,
Robert Jenssen
:
Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data
Kristoffer Wickstrøm,
Eirik Agnalt Østmo,
Keyur Radiya,
Karl Øyvind Mikalsen,
Michael Kampffmeyer,
Robert Jenssen
:
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
Kristoffer Wickstrøm,
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Ahcene Boubekki,
Karl Øyvind Mikalsen,
Michael Kampffmeyer
m.fl.:
RELAX: Representation Learning Explainability
Kristoffer Wickstrøm,
Sigurd Eivindson Løkse,
Michael Kampffmeyer,
Shujian Yu,
José C. Príncipe,
Robert Jenssen
:
Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy
Rogelio Andrade Mancisidor,
Michael Christian Kampffmeyer,
Kjersti Aas,
Robert Jenssen
:
Discriminative multimodal learning via conditional priors in generative models
Kristoffer Vinther Olesen,
Ahcene Boubekki,
Michael Christian Kampffmeyer,
Robert Jenssen,
Anders Nymark Christensen,
Sune Hørlück
m.fl.:
A Contextually Supported Abnormality Detector for Maritime Trajectories
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu,
Eric Xing
:
Federated Partially Supervised Learning With Limited Decentralized Medical Images
Daniel Johansen Trosten,
Rwiddhi Chakraborty,
Sigurd Eivindson Løkse,
Kristoffer Wickstrøm,
Robert Jenssen,
Michael Kampffmeyer
:
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings
Eirik Agnalt Østmo,
Kristoffer Wickstrøm,
Keyur Radiya,
Michael Kampffmeyer,
Robert Jenssen
:
View it like a radiologist: Shifted windows for deep learning augmentation of CT images
Daniel Johansen Trosten,
Sigurd Eivindson Løkse,
Robert Jenssen,
Michael Kampffmeyer
:
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering
Stine Hansen,
Srishti Gautam,
Suaiba Amina Salahuddin,
Michael Christian Kampffmeyer,
Robert Jenssen
:
ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement
Haoyuan Li,
Haoye Dong,
Hanchao Jia,
Dong Huang,
Michael Christian Kampffmeyer,
Liang Lin
m.fl.:
Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos
IEEE International Conference on Computer Vision (ICCV) 2023 ARKIV
Xujie Zhang,
Binbin Yang,
Michael Christian Kampffmeyer,
Wenqing Zhang,
Shiyue Zhang,
Guansong Lu
m.fl.:
DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment
IEEE International Conference on Computer Vision (ICCV) 2023 ARKIV
Luca Tomasetti,
Stine Hansen,
Mahdieh Khanmohammadi,
Kjersti Engan,
Liv Jorunn Høllesli,
Kathinka Dæhli Kurz
m.fl.:
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation
Durgesh Kumar Singh,
Ahcene Boubekki,
Robert Jenssen,
Michael Kampffmeyer
:
Supercm: Revisiting Clustering for Semi-Supervised Learning
Jonas Lederer,
Michael Gastegger,
Kristof T. Schütt,
Michael Christian Kampffmeyer,
Klaus-Robert Müller,
Oliver T. Unke
:
Automatic identification of chemical moieties
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu,
Eric Xing
:
Negational symmetry of quantum neural networks for binary pattern classification
Nanqing Dong,
Michael Kampffmeyer,
Irina Voiculescu
:
Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images
Lecture Notes in Computer Science (LNCS) 2022 DOI
Srishti Gautam,
Ahcene Boubekki,
Stine Hansen,
Suaiba Amina Salahuddin,
Robert Jenssen,
Marina Marie-Claire Hohne
m.fl.:
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model
Srishti Gautam,
Marina Marie-Claire Hohne,
Stine Hansen,
Robert Jenssen,
Michael Kampffmeyer
:
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation
Srishti Gautam,
Marina Marie-Claire Hohne,
Stine Hansen,
Robert Jenssen,
Michael Kampffmeyer
:
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation
IEEE International Symposium on Biomedical Imaging 2022 DOI
Qinghui Liu,
Michael Kampffmeyer,
Robert Jenssen,
Arnt Børre Salberg
:
Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks
International Journal of Remote Sensing 2022 DOI
Suaiba Amina Salahuddin,
Stine Hansen,
Srishti Gautam,
Michael Kampffmeyer,
Robert Jenssen
:
A self-guided anomaly detection-inspired few-shot segmentation network
CEUR Workshop Proceedings 2022 ARKIV
Xujie Zhang,
Yu Sha,
Michael Kampffmeyer,
Zhenyu Xie,
Zequn Jie,
Chengwen Huang
m.fl.:
ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design
SIGMM Records 2022
Xiao Dong,
Xunlin Zhan,
Yangxin Wu,
Yunchao Wei,
Michael Kampffmeyer,
Xiaoyong Wei
m.fl.:
M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining
Computer Vision and Pattern Recognition 2022 DOI
Zaiyu Huang,
Hanhui Li,
Zhenyu Xie,
Michael Kampffmeyer,
Qingling Cai,
Xiaodan Liang
:
Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning
Advances in Neural Information Processing Systems 2022 DOI
Arnt-Børre Salberg,
Michael Christian Kampffmeyer
:
Trends in deep learning
2023
Michael Christian Kampffmeyer
:
Learning from limited labeled data for few-shot medical image segmentation (and beyond)
2023
Magnus Oterhals Størdal,
Benjamin Ricaud,
Michael Christian Kampffmeyer,
Geir Bertelsen,
Maja Gran Erke
:
Risk Prediction of Diabetic Retinopathy in the Tromsø Study
2023
Changkyu Choi,
Michael Christian Kampffmeyer,
Nils Olav Handegard,
Arnt-Børre Salberg,
Robert Jenssen
:
Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
2023
Fredrik Emil Aspheim,
Luigi Tommaso Luppino,
Michael Christian Kampffmeyer,
Robert Jenssen,
Rune Sundset,
Akos Samuel Kuttner
:
Interpretable deep learning model for input function estimation in small-animal 18F-FDG PET imaging
2023
Ingeborg Mathiesen,
Theodor Anton Ross,
Anna Kaarina Pöntinen,
Einar Holsbø,
Michael Kampffmeyer,
Mona Johannessen
m.fl.:
Characterization of Putative Virulence Factors in Enterococcus faecium
2023
Fredrik Emil Aspheim,
Samuel Kuttner,
Luigi Tommaso Luppino,
Rune Sundset,
Michael Christian Kampffmeyer,
Robert Jenssen
:
Deep learning derived input-function in dynamic PET-imaging
2023
Michael Christian Kampffmeyer
:
UiT Machine Learning Group
2023
Michael Christian Kampffmeyer
:
Deep Clustering
2023
Michael Christian Kampffmeyer
:
Hva er kunstig intelligens (KI)? Muligheter og utfordringer
2023
Michael Christian Kampffmeyer
:
Self-Explainable Deep Learning
2023
Michael Christian Kampffmeyer
:
Learning from limited labelled data for medical image segmentation
2023
Michael Christian Kampffmeyer
:
AI’S FUTURE PATH, WHAT ARE THE OPPORTUNITIES?
2023
Michael Christian Kampffmeyer
:
Deep Multi-view Clustering
2023
Magnus Oterhals Størdal,
Benjamin Ricaud,
Michael Christian Kampffmeyer,
Geir Bertelsen,
Maja Gran Erke
:
Risk Prediction of Diabetic Retinopathy in the Tromsø Study
2023
Theodor Anton Ross,
Anna Kaarina Pöntinen,
Jessin Janice,
Einar Holsbø,
Jukka Corander,
Kristin Hegstad
m.fl.:
Leveraging machine learning for finding novel putative virulence factors in Enterococcus faecium
2022
Changkyu Choi,
Shujian Yu,
Michael Kampffmeyer,
Arnt-Børre Salberg,
Nils Olav Handegard,
Suaiba Amina Salahuddin
m.fl.:
Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior
2022
Srishti Gautam,
Marina Marie-Claire Hohne,
Stine Hansen,
Robert Jenssen,
Michael Kampffmeyer
:
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation
2022
Srishti Gautam,
Marina Marie-Claire Hohne,
Stine Hansen,
Robert Jenssen,
Michael Kampffmeyer
:
Artifact Detection with Prototypical Relevance Propagation
2022
Srishti Gautam,
Marina Marie-Claire Hohne,
Stine Hansen,
Robert Jenssen,
Michael Kampffmeyer
:
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation
2022
Samuel Kuttner,
Luigi Tommaso Luppino,
Kristoffer Wickstrøm,
Nils Thomas Doherty Midtbø,
Seyed Esmaeil Dorraji,
Ana Oteiza
m.fl.:
Deep learning derived input function in dynamic 18F-FDG PET imaging of mice
2022
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