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Sebastian Stober
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Deep feature learning for EEG recordings
S Stober, A Sternin, AM Owen, JA Grahn
arXiv preprint arXiv:1511.04306, 2015
1672015
Using Convolutional Neural Networks to Recognize Rhythm Stimuli from Electroencephalography Recordings
S Stober, DJ Cameron, JA Grahn
Advances in neural information processing systems 27, 2014
1252014
Transfer learning for speech recognition on a budget
J Kunze, L Kirsch, I Kurenkov, A Krug, J Johannsmeier, S Stober
arXiv preprint arXiv:1706.00290, 2017
1202017
Designing gaze-supported multimodal interactions for the exploration of large image collections
S Stellmach, S Stober, A Nürnberger, R Dachselt
Proceedings of the 1st conference on novel gaze-controlled applications, 1-8, 2011
672011
Moving beyond ERP components: a selective review of approaches to integrate EEG and behavior
DA Bridwell, JF Cavanagh, AGE Collins, MD Nunez, R Srinivasan, ...
Frontiers in human neuroscience 12, 106, 2018
502018
Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net
N Aldoj, F Biavati, F Michallek, S Stober, M Dewey
Scientific reports 10 (1), 1-17, 2020
422020
Deep learning based on event-related EEG differentiates children with ADHD from healthy controls
A Vahid, A Bluschke, V Roessner, S Stober, C Beste
Journal of clinical medicine 8 (7), 1055, 2019
422019
Towards Query by Singing/Humming on Audio Databases.
A Duda, A Nürnberger, S Stober
ISMIR, 331-334, 2007
422007
Towards Music Imagery Information Retrieval: Introducing the OpenMIIR Dataset of EEG Recordings from Music Perception and Imagination.
S Stober, A Sternin, AM Owen, JA Grahn
ISMIR, 763-769, 2015
402015
Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control
A Vahid, M Mückschel, S Stober, AK Stock, C Beste
Communications biology 3 (1), 1-11, 2020
372020
Classifying EEG Recordings of Rhythm Perception.
S Stober, DJ Cameron, JA Grahn
ISMIR, 649-654, 2014
352014
Learning discriminative features from electroencephalography recordings by encoding similarity constraints
S Stober
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
332017
Adaptive music retrieval–a state of the art
S Stober, A Nürnberger
Multimedia Tools and Applications 65 (3), 467-494, 2013
322013
The hubness phenomenon: Fact or artifact?
T Low, C Borgelt, S Stober, A Nürnberger
Towards Advanced Data Analysis by Combining Soft Computing and Statistics …, 2013
302013
Towards user-adaptive structuring and organization of music collections
S Stober, A Nürnberger
International Workshop on Adaptive Multimedia Retrieval, 53-65, 2008
282008
Exploration of interpretability techniques for deep covid-19 classification using chest x-ray images
S Chatterjee, F Saad, C Sarasaen, S Ghosh, R Khatun, P Radeva, ...
arXiv preprint arXiv:2006.02570, 2020
272020
MusicGalaxy–an adaptive user-interface for exploratory music retrieval
S Stober, A Nürnberger
Proc. of 7th Sound and Music Computing conference (SMC’10), 2010
262010
Carsa–an architecture for the development of context adaptive retrieval systems
K Bade, EWD Luca, A Nürnberger, S Stober
International Workshop on Adaptive Multimedia Retrieval, 91-101, 2005
242005
User-aware music retrieval
M Schedl, S Stober, E Gómez, N Orio, C Liem
Dagstuhl Follow-Ups 3, 2012
222012
An experimental comparison of similarity adaptation approaches
S Stober, A Nürnberger
International Workshop on Adaptive Multimedia Retrieval, 96-113, 2011
202011
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