Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning objects into groups or clusters, such that objects in the same group are more similar to one another than ...
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We present a deep-learning method based on Wiener filters and U-Nets that performs image reconstruction in systems with spatially-varying aberrations. We train on simulated microscopy measurements and test on experime...
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Wireless technology gradual growth in the latest years has facilitated it to bridge its applications operated extensively in many types of industry. Wireless sensor network (WSN) technology brings several benefits ove...
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The growing increase in energy consumption and the concern for the environment have driven research and use of renewable sources of energy. Within the concept of the use of renewable energy sources, the integration of...
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Digital breast tomosynthesis is a novel breast cancer detection technique by allowing the reconstruction of arbitrary planes in the breast from a set of limited-angle projection images acquired at different view angle...
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This paper presents the evaluation of seven techniques of feature extraction (PSD, F-Test, EMD, MCE, CCA, LASSO and MSI) for gaze-target detections in a SSVEP-based BCI. Two type of technologies for visual stimulation...
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This paper presents the evaluation of seven techniques of feature extraction (PSD, F-Test, EMD, MCE, CCA, LASSO and MSI) for gaze-target detections in a SSVEP-based BCI. Two type of technologies for visual stimulation were used (LCD and LEDs). Five differents windows lengths (1, 2, 4, 5 and 10 s) were used and seven volunteers participated in this study. The highest accuracy obtained in all cases was 93.57% using LEDs and the highest ITR was 36.90 bits/min for LCD. The technique based on MSI shows the highest success rate in both cases (LCD or LED) and is even more noticeable when the window size is increased.
In recent years, object detection approaches using deep convolutional neural networks (CNNs) have derived major advances in normal images. However, such success is hardly achieved with rainy images due to lack of visi...
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This paper presents the comparation of three different feature extraction techniques based on the Empirical Mode Decomposition (EMD) for a SSVEP-BCI. This approach based on the characterization of the signal by EMD, i...
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ISBN:
(纸本)9781479924004
This paper presents the comparation of three different feature extraction techniques based on the Empirical Mode Decomposition (EMD) for a SSVEP-BCI. This approach based on the characterization of the signal by EMD, is proposed as a novel alternative to other techniques and it was demonstrated that it exceeds both in accuracy rate and Information Transfer Rate (ITR). The experiments were performed in an offline way, and seven volunteers participated of the study. The stimulis were generated both by LCD and LEDs. The frequencies used were 8, 11, 13 and 15 Hz. The results here reported such represent the average of the seven participants, achieving a success rate of 81% and ITR of 23.32 bits/min of the total set of cases analyzed. It is further confirmed that the highest success rates and ITRs were obtained for stimulation by LEDs.
Increasing penetration of wind and renewable generation poses significant challenges to the power system operations and reliability. This paper considers the real-time optimal transmission switching (OTS) problem for ...
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