Sebastian Stober
Cited by
Cited by
Deep feature learning for EEG recordings
S Stober, A Sternin, AM Owen, JA Grahn
arXiv preprint arXiv:1511.04306, 2015
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
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
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), 14315, 2020
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
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
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
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), 112, 2020
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
Classifying EEG Recordings of Rhythm Perception.
S Stober, DJ Cameron, JA Grahn
ISMIR, 649-654, 2014
Towards Query by Singing/Humming on Audio Databases.
A Duda, A Nürnberger, S Stober
ISMIR, 331-334, 2007
Exploration of interpretability techniques for deep covid-19 classification using chest x-ray images
S Chatterjee, F Saad, C Sarasaen, S Ghosh, V Krug, R Khatun, R Mishra, ...
Journal of imaging 10 (2), 2024
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
Learning discriminative features from electroencephalography recordings by encoding similarity constraints
S Stober
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
Musicgalaxy: A multi-focus zoomable interface for multi-facet exploration of music collections
S Stober, A Nürnberger
Exploring Music Contents: 7th International Symposium, CMMR 2010, Málaga …, 2011
Adaptive music retrieval–a state of the art
S Stober, A Nürnberger
Multimedia Tools and Applications 65, 467-494, 2013
MusicGalaxy–an adaptive user-interface for exploratory music retrieval
S Stober, A Nürnberger
Proc. of 7th Sound and Music Computing conference (SMC’10), 2010
Towards user-adaptive structuring and organization of music collections
S Stober, A Nürnberger
International Workshop on Adaptive Multimedia Retrieval, 53-65, 2008
Prednet and predictive coding: A critical review
RP Rane, E Szügyi, V Saxena, A Ofner, S Stober
Proceedings of the 2020 international conference on multimedia retrieval …, 2020
Neuron activation profiles for interpreting convolutional speech recognition models
A Krug, R Knaebel, S Stober
NeurIPS Workshop on Interpretability and Robustness in Audio, Speech, and …, 2018
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