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Sepideh Kilani, Seyedeh Nadia Aghili and Mircea Hulea
A new approach is introduced to address the subject dependency problem in P300-based brain-computer interfaces (BCI) by using transfer learning. The occurrence of P300, an event-related potential, is primarily associated with changes in natural neuron ac...
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Rito Clifford Maswanganyi, Chungling Tu, Pius Adewale Owolawi and Shengzhi Du
Transfer learning (TL) has been proven to be one of the most significant techniques for cross-subject classification in electroencephalogram (EEG)-based brain-computer interfaces (BCI). Hence, it is widely used to address the challenges of cross-session ...
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Marcin Kolodziej, Andrzej Majkowski, Remigiusz J. Rak and Przemyslaw Wiszniewski
One approach employed in brain?computer interfaces (BCIs) involves the use of steady-state visual evoked potentials (SSVEPs). This article examines the capability of artificial intelligence, specifically convolutional neural networks (CNNs), to improve S...
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Woo-Sung Choi and Hong-Gi Yeom
A brain?computer interface (BCI) is a promising technology that can analyze brain signals and control a robot or computer according to a user?s intention. This paper introduces our studies to overcome the challenges of using BCIs in daily life. There are...
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Ramesh Das, Utpal Das
Pág. 68 - 83
The countries in the world in the globalized era have faced heterogeneity in challenges in managing their growth factors as well as the stake holders of such growth profiles. The political and economic turmoil of the last two decades around the world hav...
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