scholarly journals A novel optical labeling scheme using a FSK modulated DFB laser integrated with an EA modulator

Author(s):  
J. Zhang ◽  
N. Chi ◽  
P. Holm-Nielsen ◽  
C. Peucheret ◽  
P. Jeppesen
Keyword(s):  
2014 ◽  
Vol 1 (1) ◽  
pp. 89 ◽  
Author(s):  
Dong-ling Xu ◽  
Chris Foster ◽  
Ying Hu ◽  
Jian-bo Yang

Author(s):  
Kyungkoo Jun

Background & Objective: This paper proposes a Fourier transform inspired method to classify human activities from time series sensor data. Methods: Our method begins by decomposing 1D input signal into 2D patterns, which is motivated by the Fourier conversion. The decomposition is helped by Long Short-Term Memory (LSTM) which captures the temporal dependency from the signal and then produces encoded sequences. The sequences, once arranged into the 2D array, can represent the fingerprints of the signals. The benefit of such transformation is that we can exploit the recent advances of the deep learning models for the image classification such as Convolutional Neural Network (CNN). Results: The proposed model, as a result, is the combination of LSTM and CNN. We evaluate the model over two data sets. For the first data set, which is more standardized than the other, our model outperforms previous works or at least equal. In the case of the second data set, we devise the schemes to generate training and testing data by changing the parameters of the window size, the sliding size, and the labeling scheme. Conclusion: The evaluation results show that the accuracy is over 95% for some cases. We also analyze the effect of the parameters on the performance.


1988 ◽  
Vol 24 (8) ◽  
pp. 495 ◽  
Author(s):  
H. Ishikawa ◽  
K. Kamite ◽  
K. Kihara ◽  
H. Soda ◽  
H. Imai
Keyword(s):  

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ross M. Lawrence ◽  
Eric W. Bridgeford ◽  
Patrick E. Myers ◽  
Ganesh C. Arvapalli ◽  
Sandhya C. Ramachandran ◽  
...  

AbstractUsing brain atlases to localize regions of interest is a requirement for making neuroscientifically valid statistical inferences. These atlases, represented in volumetric or surface coordinate spaces, can describe brain topology from a variety of perspectives. Although many human brain atlases have circulated the field over the past fifty years, limited effort has been devoted to their standardization. Standardization can facilitate consistency and transparency with respect to orientation, resolution, labeling scheme, file storage format, and coordinate space designation. Our group has worked to consolidate an extensive selection of popular human brain atlases into a single, curated, open-source library, where they are stored following a standardized protocol with accompanying metadata, which can serve as the basis for future atlases. The repository containing the atlases, the specification, as well as relevant transformation functions is available in the neuroparc OSF registered repository or https://github.com/neurodata/neuroparc.


Author(s):  
Takuma Aihara ◽  
Tatsurou Hiraki ◽  
Takuro Fujii ◽  
Koji Takeda ◽  
Tai Tsuchizawa ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document