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Ervin Sejdić
University of Pittsburgh
208Publications
24H-index
2,163Citations
Publications 208
Newest
Published on Jul 8, 2019in arXiv: Signal Processing
Published on Jun 1, 2019in Journal of Neural Engineering 3.92
Aya Khalaf3
Estimated H-index: 3
,
Ervin Sejdić24
Estimated H-index: 24
,
Murat Akcakaya10
Estimated H-index: 10
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Published on May 1, 2019 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
Elise Dagois (University of Pittsburgh), Aya Khalaf3
Estimated H-index: 3
(University of Pittsburgh)
+ 1 AuthorsMurat Akcakaya10
Estimated H-index: 10
(University of Pittsburgh)
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Published on May 1, 2019in Computers in Biology and Medicine 2.12
Zhenwei Zhang (University of Pittsburgh), Ervin Sejdić24
Estimated H-index: 24
(University of Pittsburgh)
Abstract The application of machine learning to radiological images is an increasingly active research area that is expected to grow in the next five to ten years. Recent advances in machine learning have the potential to recognize and classify complex patterns from different radiological imaging modalities such as x-rays, computed tomography, magnetic resonance imaging and positron emission tomography imaging. In many applications, machine learning based systems have shown comparable performanc...
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Published on May 1, 2019in Journal of Neuroscience Methods 2.67
Aya Khalaf3
Estimated H-index: 3
(University of Pittsburgh),
Ervin Sejdić24
Estimated H-index: 24
(University of Pittsburgh),
Murat Akcakaya10
Estimated H-index: 10
(University of Pittsburgh)
Abstract Background Recently, hybrid brain-computer interfaces (BCIs) combining more than one modality have been investigated with the aim of boosting the performance of the existing single-modal BCIs in terms of accuracy and information transfer rate (ITR). Previously, we introduced a novel hybrid BCI in which EEG and fTCD modalities are used simultaneously to measure electrical brain activity and cerebral blood velocity during motor imagery (MI) tasks. New method In this paper, we used multi-s...
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Published on Apr 8, 2019in Mathematical Problems in Engineering 1.15
Milos Dakovic15
Estimated H-index: 15
(University of Montenegro),
Ljubisa Stankovic38
Estimated H-index: 38
(University of Montenegro),
Ervin Sejdić24
Estimated H-index: 24
(University of Pittsburgh)
Analysis of vertex-varying spectral content of signals on graphs challenges the assumption of vertex invariance and requires the introduction of vertex-frequency representations as a new tool for graph signal analysis. Local smoothness, an important parameter of vertex-varying graph signals, is introduced and defined in this paper. Basic properties of this parameter are given. By using the local smoothness, an ideal vertex-frequency distribution is introduced. The local smoothness estimation is ...
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Published on Mar 27, 2019in Dysphagia 2.53
Zhenwei Zhang (University of Pittsburgh), Subashan Perera44
Estimated H-index: 44
(University of Pittsburgh)
+ 4 AuthorsErvin Sejdić24
Estimated H-index: 24
(University of Pittsburgh)
Videofluoroscopic swallow studies are widely used in clinical and research settings to assess swallow function and to determine physiological impairments, diet recommendations, and treatment goals for people with dysphagia. Videofluoroscopy can be used to analyze biomechanical events of swallowing, including hyoid bone displacement, to differentiate between normal and disordered swallow functions. Previous research has found significant associations between hyoid bone displacement and penetratio...
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Published on Mar 26, 2019in arXiv: Signal Processing
Ljubisa Stankovic38
Estimated H-index: 38
,
Danilo P. Mandic44
Estimated H-index: 44
+ 3 AuthorsAnthony G. Constantinides25
Estimated H-index: 25
Graphs are irregular structures which naturally account for data integrity, however, traditional approaches have been established outside Signal Processing, and largely focus on analyzing the underlying graphs rather than signals on graphs. Given the rapidly increasing availability of multisensor and multinode measurements, likely recorded on irregular or ad-hoc grids, it would be extremely advantageous to analyze such structured data as graph signals and thus benefit from the ability of graphs ...
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