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D-Index & Metrics

Computer Science

D-Index
32
Citations
6496
World Ranking
12944
National Ranking
244

Overview

Marco Loog is a researcher affiliated with Radboud University in the Netherlands. Their work spans numerous publications primarily in the field of computer science, with a specific focus on artificial intelligence and machine learning. The breadth of their research includes subfields such as computer vision and pattern recognition, molecular biology, cancer research, and computational theory and mathematics.

The scientist's research topics cover multiple areas within machine learning and data analysis. Key topics include machine learning and data classification, machine learning algorithms, domain adaptation and few-shot learning, anomaly detection techniques and applications, cancer genomics and diagnostics, explainable artificial intelligence (XAI), and cell image analysis techniques.

Marco Loog's publication record features numerous articles, including recent papers such as:

  • The Shape of Learning Curves: A Review, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Predicting patient response with models trained on cell lines and patient-derived xenografts by nonlinear transfer learning, 2021, Proceedings of the National Academy of Sciences
  • Improved Generalization in Semi-Supervised Learning: A Survey of Theoretical Results, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Seismic inversion with deep learning, 2021, Computational Geosciences
  • Resolution Learning in Deep Convolutional Networks Using Scale-Space Theory, 2021, IEEE Transactions on Image Processing

Their frequent coauthors include Tom J. Viering, Soufiane Mourragui, Lodewyk F.A. Wessels, Alexander Mey, and David M. J. Tax. This collaboration network highlights an engaged research environment within related topics and methods.

Marco Loog has contributed regularly to prominent publication venues, with a notable presence in arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the National Academy of Sciences, and Computational Geosciences.

The profile of Marco Loog reflects a focused engagement in the interdisciplinary application of machine learning, encompassing both theoretical advancements and applied methodologies in areas intersecting biology, medicine, and computational sciences.

Best Publications

  • Comparative study of retinal vessel segmentation methods on a new publicly available database

    Meindert Niemeijer;Meindert Niemeijer;Joes Staal;Bram van Ginneken;Marco Loog

  • Multiclass linear dimension reduction by weighted pairwise Fisher criteria

    M. Loog;R.P.W. Duin;R. Haeb-Umbach

  • A Review of Domain Adaptation without Target Labels

    Unknown

  • Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion

    R.P.W. Duin;M. Loog

  • Quantitative Comparison of Spot Detection Methods in Fluorescence Microscopy

    I. Smal;M. Loog;W. Niessen;E. Meijering

  • A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database.

    Arnold M.R. Schilham;Bram van Ginneken;Marco Loog

  • Deep Learning and Data Labeling for Medical Applications

    Gustavo Carneiro;Diana Mateus;Loïc Peter;Andrew Bradley

  • On Combining Computer-Aided Detection Systems

    Meindert Niemeijer;Marco Loog;Michael David Abràmoff;Max A Viergever

  • Multiple instance learning with bag dissimilarities

    Veronika Cheplygina;David M.J. Tax;Marco Loog

  • A benchmark and comparison of active learning for logistic regression

    Unknown

  • Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification

    M. Loog;B. Ginneken

  • PRECISE: a domain adaptation approach to transfer predictors of drug response from pre-clinical models to tumors.

    Soufiane Mourragui;Soufiane Mourragui;Marco Loog;Marco Loog;Mark A van de Wiel;Mark A van de Wiel;Marcel J T Reinders;Marcel J T Reinders

  • Multi-spectral video endoscopy system for the detection of cancerous tissue

    Raimund Leitner;Martin De Biasio;Thomas Arnold;Cuong Viet Dinh

  • Local Fisher embedding

    D. de Ridder;M. Loog;M.J.T. Reinders

  • On the Behavior of Spatial Critical Points under Gaussian Blurring. A Folklore Theorem and Scale-Space Constraints

    Marco Loog;Johannes Jisse Duistermaat;Luc Florack

  • A variance maximization criterion for active learning

    Unknown

  • Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification

    Unknown

  • Active learning using uncertainty information

    Unknown

  • Multiple-instance learning as a classifier combining problem

    Yan Li;David M. J. Tax;Robert P. W. Duin;Marco Loog

  • Dissimilarity-Based Ensembles for Multiple Instance Learning

    Veronika Cheplygina;David M. J. Tax;Marco Loog

  • Feature-level domain adaptation

    Wouter M. Kouw;Laurens J. P. Van Der Maaten;Jesse H. Krijthe;Marco Loog

  • Breast tissue density measure

    Jakob Raundahl;Marco Loog;Mads Nielsen

  • Single- vs. multiple-instance classification

    Ethem Alpaydın;Veronika Cheplygina;Marco Loog;David M.J. Tax

  • On classification with bags, groups and sets

    Veronika Cheplygina;David M.J. Tax;Marco Loog

  • Early diagnosis of dementia based on intersubject whole-brain dissimilarities

    S. Klein;M. Loog;F. van der Lijn;T. den Heijer

Frequent Co-Authors

Robert P. W. Duin
Robert P. W. Duin Delft University of Technology
Mads Nielsen
Mads Nielsen University of Copenhagen
David M. J. Tax
David M. J. Tax Delft University of Technology
Marleen de Bruijne
Marleen de Bruijne Erasmus University Rotterdam
De-Shuang Huang
De-Shuang Huang Tongji University
Marcel J. T. Reinders
Marcel J. T. Reinders Delft University of Technology
Fabio Roli
Fabio Roli University of Genoa
Christian Igel
Christian Igel University of Copenhagen
Lodewyk F. A. Wessels
Lodewyk F. A. Wessels Antoni van Leeuwenhoek Hospital
Paolo Brambilla
Paolo Brambilla University of Milan

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