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| * '''Brain–computer interfaces in neurological rehabilitation''' [[attachment:MLBE14_bci.pdf]] (additional material: [[attachment:MLBE14_bci.zip]]) * '''Bag-of-words representation for biomedical time series''' * '''Change-Point Detection''' * '''Image-Based Cytometry''' * '''ECG Analysis''' * '''Myoelectric Control of Prostheses''' * '''Fingerprints''' * '''Histopathological Image Analysis''' * '''Hidden Markov Models''' * '''Monte Carlo Methods''' * '''Analysis of Microarray Data''' * '''Monte Carlo Methods''' * '''Quality assessment using EEG''' * '''Segmentation of MRI''' * '''Biomedical Sensors''' * '''Wavelets Analysis''' |
* '''Brain–computer interfaces''' [[attachment:MLBE14_bci.pdf]] (additional material: [[attachment:MLBE14_bci.zip]]) * '''Bag-of-words representation''' [[attachment:MLBE14_bow.pdf]] * '''Analysis of Changes''' [[attachment:MLBE14_change.pdf]] * '''Image-Based Cytometry''' [[attachment:MLBE14_cytometry.pdf]] * '''ECG Analysis''' [[attachment:MLBE14_ecg.pdf]] * '''Myoelectric Control of Prostheses''' [[attachment:MLBE14_emg.pdf]] * '''Fingerprints''' [[attachment:MLBE14_fingerprint.pdf]] * '''Histopathological Image Analysis''' [[attachment:MLBE14_histo.pdf]] * '''Hidden Markov Models''' [[attachment:MLBE14_hmm.pdf]] * '''Monte Carlo Methods''' [[attachment:MLBE14_mc.pdf]] * '''Analysis of Microarray Data''' [[attachment:MLBE14_microarray.pdf]] * '''Quality assessment using EEG''' [[attachment:MLBE14_quality.pdf]] * '''Segmentation of MRI''' [[attachment:MLBE14_mri.pdf]] * '''Biomedical Sensors''' [[attachment:MLBE14_sensors.pdf]] * '''Wavelets Analysis''' [[attachment:MLBE14_wavelets.pdf]] |
Block-Seminar "Machine Learning for Biomedical Engineering"
Termine und Informationen
Erster Termin für Themenvergabe |
Montag, 28.04.2014, 10:00 in MAR 4.033 |
Verantwortlich |
Prof. Dr. Klaus-Robert Müller |
Dozent: |
Wojciech Samek (wojciech.samek@tu-berlin.de, Raum MAR 4.060) |
Sprache |
Englisch |
This seminar takes a closer look at specific applications of machine learning algorithms in the field of biomedical engineering.
Students will read, understand, evaluate and present selected research papers on machine learning methods in different applications settings. At the end of the semester, each student will present his/her topic in a 20 min talk (+ 10 min discussion) in English.
The topics of the seminar are:
Brain–computer interfaces MLBE14_bci.pdf (additional material: MLBE14_bci.zip)
Bag-of-words representation MLBE14_bow.pdf
Analysis of Changes MLBE14_change.pdf
Image-Based Cytometry MLBE14_cytometry.pdf
ECG Analysis MLBE14_ecg.pdf
Myoelectric Control of Prostheses MLBE14_emg.pdf
Fingerprints MLBE14_fingerprint.pdf
Histopathological Image Analysis MLBE14_histo.pdf
Hidden Markov Models MLBE14_hmm.pdf
Monte Carlo Methods MLBE14_mc.pdf
Analysis of Microarray Data MLBE14_microarray.pdf
Quality assessment using EEG MLBE14_quality.pdf
Segmentation of MRI MLBE14_mri.pdf
Biomedical Sensors MLBE14_sensors.pdf
Wavelets Analysis MLBE14_wavelets.pdf