Face image recognition based on time series motif discovery

2012 ◽  
Author(s):  
Lianhua Chi ◽  
Yucai Feng ◽  
Hehua Chi ◽  
Ying Huang
Keyword(s):  
Time Series ◽  
Image Recognition ◽  
Motif Discovery ◽  
Face Image

New Techniques for Face Image Recognition Identification and Labeling

2007 ◽  
Vol 1 (4) ◽  
pp. 62-69
Author(s):  
Milhled Alfaouri ◽  
◽  
Nada N. Al-Ramahi ◽  
Keyword(s):  
Image Recognition ◽  
Face Image ◽  
New Techniques

Performance Evaluation Of Face Image Recognition Based Voila-Joins With SVM

2019 ◽  
pp. 161
Author(s):  
Jamal Mustafa Al-Tuwaijari ◽  
Suhad Ibrahim Mohammed
Keyword(s):  
Performance Evaluation ◽  
Image Recognition ◽  
Face Image

Survey on time series motif discovery

2017 ◽  
Vol 7 (2) ◽  
pp. e1199 ◽  
Author(s):  
Sahar Torkamani ◽  
Volker Lohweg
Keyword(s):  
Time Series ◽  
Motif Discovery

scholarly journals FEATURES OF DERIVATIVE CONTINUITY IN SHAPE

1999 ◽  
Vol 13 (08) ◽  
pp. 1181-1199
Author(s):  
PHILIP F. HENSHAW
Keyword(s):  
Time Series ◽  
Image Recognition ◽  
Scale Space ◽  
Complex Processes ◽  
Behavioral Dynamics ◽  
Higher Derivative ◽  
Smoothing Kernel ◽  
Key Features ◽  
Invariant Relationship ◽  
Gaussian Scale Space

Derivative continuity is a distributed invariant relationship between parts of flowing shapes. The original techniques presented here were developed for making the behavioral dynamics of complex processes more recognizable, but are equally applicable to assisting in the recognition of shapes in images. Regularizing a sequence using a constraint of derivative continuity is equivalent to using a bimodal smoothing kernel, producing a distinct bias for reducing variation on higher derivative levels, sharply defining shape with minimal suppression of shape. To help determine where reconstructing shapes in this way is valid, a test was developed to help distinguish combinations of noise and smooth flows from random walks. This helps distinguish between illusory and genuine, data shapes but also exposes a flair in using this and other measures of scaling behavior for diagnostic purposes. Gaussian scale space techniques in use for some time in image recognition, for identifying reliable landmarks in the shapes of outlines, are demonstrated for use in identifying key features of shape in time series.

scholarly journals Accelerating time series motif discovery in the Intel Xeon Phi KNL processor

2019 ◽  
Vol 75 (11) ◽  
pp. 7053-7075 ◽  
Author(s):  
Ivan Fernandez ◽  
Alejandro Villegas ◽  
Eladio Gutierrez ◽  
Oscar Plata
Keyword(s):  
Time Series ◽  
Motif Discovery ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Intel Xeon
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