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Friedhelm Schwenker

Friedhelm Schwenker

D-Index & Metrics

Computer Science

D-Index
43
Citations
7271
World Ranking
8022
National Ranking
392

Overview

Friedhelm Schwenker is affiliated with the University of Ulm in Germany. Their research primarily spans the fields of Computer Science and Medicine, with a particular focus on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Experimental and Cognitive Psychology, and Signal Processing.

The scientist's work covers several specialized topics including:

  • AI in cancer detection
  • Emotion and Mood Recognition
  • EEG and Brain-Computer Interfaces
  • Anomaly Detection Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging
  • COVID-19 diagnosis using AI
  • Machine Learning and Data Classification

Frequent co-authors collaborating with Schwenker include:

  • Peter Bellmann
  • Patrick Thiam
  • Ram Sarkar
  • Taye Girma Debelee
  • Hans A. Kestler

Schwenker has published extensively in several venues. The most common publication outlets are:

  • IEEE Access
  • Zenodo (CERN European Organization for Nuclear Research)
  • Sensors
  • arXiv (Cornell University)
  • Applied Sciences

Recent notable publications include:

  • "A Survey of Brain Tumor Segmentation and Classification Algorithms," 2021, Journal of Imaging
  • "Enhanced Region Growing for Brain Tumor MR Image Segmentation," 2021, Journal of Imaging
  • "Interpretable Machine Learning Techniques in ECG-Based Heart Disease Classification: A Systematic Review," 2022, Diagnostics
  • "Deep Learning in Selected Cancers' Image Analysis-A Survey," 2020, Journal of Imaging
  • "Comparison of short-term electrical load forecasting methods for different building types," 2021, Energy Informatics

In addition to journal publications, Schwenker has contributed to book literature published by Springer Science+Business Media. One recent contribution is the 2024 volume titled "Pan-African Conference on Artificial Intelligence."

Best Publications

  • Three learning phases for radial-basis-function networks

    Friedhelm Schwenker;Hans A. Kestler;Günther Palm

  • Pattern classification and clustering: A review of partially supervised learning approaches

    Friedhelm Schwenker;Edmondo Trentin

  • Hierarchical support vector machines for multi-class pattern recognition

    F. Schwenker

  • A dataset of continuous affect annotations and physiological signals for emotion analysis.

    Karan Sharma;Karan Sharma;Claudio Castellini;Egon L. van den Broek;Alin Albu-Schaeffer

  • Multiple classifier systems for the classificatio of audio-visual emotional states

    Michael Glodek;Stephan Tschechne;Georg Layher;Martin Schels

  • A Survey of Brain Tumor Segmentation and Classification Algorithms.

    Erena Siyoum Biratu;Friedhelm Schwenker;Yehualashet Megersa Ayano;Taye Girma Debelee;Taye Girma Debelee

  • Survey of deep learning in breast cancer image analysis

    Taye Girma Debelee;Friedhelm Schwenker;Achim Ibenthal;Dereje Yohannes

  • Semi-supervised Learning

    Mohamed Farouk Abdel Hady;Friedhelm Schwenker

  • Iterative retrieval of sparsely coded associative memory patterns

    F. Schwenker;F. T. Sommer;G. Palm

  • Enhanced Region Growing for Brain Tumor MR Image Segmentation

    Erena Siyoum Biratu;Friedhelm Schwenker;Taye Girma Debelee;Taye Girma Debelee;Samuel Rahimeto Kebede

  • Ensemble Methods: Foundations and Algorithms [Book Review]

    Friedhelm Schwenker

  • Methods for Person-Centered Continuous Pain Intensity Assessment From Bio-Physiological Channels

    Markus Kachele;Patrick Thiam;Mohammadreza Amirian;Friedhelm Schwenker

  • A study of the robustness of KNN classifiers trained using soft labels

    Neamat El Gayar;Friedhelm Schwenker;Günther Palm

  • Exploring Deep Physiological Models for Nociceptive Pain Recognition.

    Patrick Thiam;Peter Bellmann;Hans A. Kestler;Friedhelm Schwenker

  • Adaptive confidence learning for the personalization of pain intensity estimation systems

    Markus Kächele;Mohammadreza Amirian;Patrick Thiam;Philipp Werner

  • Investigating fuzzy-input fuzzy-output support vector machines for robust voice quality classification

    Stefan Scherer;John Kane;Christer Gobl;Friedhelm Schwenker

  • Multimodal emotion classification in naturalistic user behavior

    Steffen Walter;Stefan Scherer;Martin Schels;Michael Glodek

  • Co-training by Committee: A New Semi-supervised Learning Framework

    M. Hady;F. Schwenker

  • De-noising of high-resolution ECG signals by combining the discrete wavelet transform with the Wiener filter

    H.A. Kestler;M. Haschka;W. Kratz;F. Schwenker

  • Combining committee-based semi-supervised learning and active learning

    Mohamed Farouk Abdel Hady;Friedhelm Schwenker

  • The SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain- and Emotion-Recognition System

    Maria Velana;Sascha Gruss;Georg Layher;Patrick Thiam

  • Emotion Recognition from Speech

    Andreas Wendemuth;Bogdan Vlasenko;Ingo Siegert;Ronald Böck

Frequent Co-Authors

Günther Palm
Günther Palm University of Ulm
Hans A. Kestler
Hans A. Kestler University of Ulm
Heiko Neumann
Heiko Neumann University of Ulm
Ram Sarkar
Ram Sarkar Jadavpur University
Claudio Castellini
Claudio Castellini University of Erlangen-Nuremberg
Louis-Philippe Morency
Louis-Philippe Morency Carnegie Mellon University
Klaus Dietmayer
Klaus Dietmayer University of Ulm
Nick Campbell
Nick Campbell Trinity College Dublin
Michael Weber
Michael Weber University of Ulm

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