scholarly journals A Strange Algorithm for Fingerprint Based Age Estimation using Frequency Domain and Pattern Recognition Techniques

2019 ◽  
Vol 8 (2S3) ◽  
pp. 1354-1358
Keyword(s):  
Pattern Recognition ◽  
Frequency Domain ◽  
Age Estimation ◽  
Independent Component ◽  
Two Dimensional ◽  
Pattern Recognition Techniques ◽  
Age Factor ◽  
Distinct Person

identifying the age from the unique mark of a new individual is a developing field of constructing studies. to perform this age component diverse systems had been extensively applied. Dominant a part of strategies makes use of the parameters like facet check and area broadness of a given particular finger influence for identity of the age estimation of that distinct person. Unique mark exam has enormous potential as a functioning machine for recognizable evidence of an person depending on both medical just as on restorative parameters. on this exploration work to select the age along their relationship recurrence vicinity and example acknowledgment methods were actualized for a hit grouping of finger prints two Dimensional Discrete Wavelet's (DWT) alongside independent component evaluation (ICA) are utilized to gauge the age factor from the unique mark statistics base. The statistics base which contains round 500 fingerprints of humans involving extraordinary age bunches inside the scope of 10 to 60 is considered for our exploration work. Multi-modular aid Vector gadget primarily based classifier is utilized for particular mark grouping. The exploratory consequences were arranged and from alongside those strains were given plots it changed into discovered that the talent of the proposed method is good.

Pattern recognition techniques applied to microdiffraction patterns

1983 ◽  
Vol 41 ◽  
pp. 302-303
Author(s):  
J.M. Cowley ◽  
W.B. Monosmith ◽  
M.M. Disko
Keyword(s):  
Pattern Recognition ◽  
Amorphous Materials ◽  
Amorphous Film ◽  
Crystal Defects ◽  
Two Dimensional ◽  
Small Particles ◽  
Regular Array ◽  
Pattern Recognition Techniques ◽  
Individual Crystal ◽  
Electron Microdiffraction

Electron microdiffraction from regions less than 20Å, and as small as 3Å, in diameter are now readily obtained with a dedicated STEM instrument, especially if an efficient two dimensional detector system is employed. Such patterns may be valuable for detailed studies of small particles, individual crystal defects and small ordered regions within microcrystalline or amorphous materials. A difficulty which often arises in the use of microdiffraction patterns is that of determining to what extent a pattern or collection of patterns is representative of the material under study. For example, for a thin amorphous film, the recording of one pattern showing a well-developed regular array of spots is not significant since the randomness of the structure ensures that any such a pattern will occur with some finite probability. To characterize the nature and extent of the local atomic ordering, statistical analysis of a very large number of patterns would be required.

Evaluation of a Fourier-Transform-Based Pattern-Recognition Algorithm for Two-Dimensional Fluorescence Data

1987 ◽  
Vol 41 (3) ◽  
pp. 496-502 ◽  
Author(s):  
Chou-Pong Pau ◽  
Isiah M. Warner
Keyword(s):  
Pattern Recognition ◽  
Correlation Function ◽  
Frequency Domain ◽  
Fourier Transforms ◽  
Recognition Algorithm ◽  
Two Dimensional ◽  
Pattern Recognition Algorithm ◽  
Absolute Value ◽  
The Absolute ◽  
Matching Criteria

A pattern-recognition algorithm for two-dimensional fluorescence data previously reported is critically evaluated. The three spectral matching criteria—sum of the absolute value of the imaginary coefficients of the frequency-domain correlation function, sum of the absolute value of the real-negative coefficients of the frequency-domain correlation function, and the intervector distance between the abbreviated Fourier transforms of two spectra—are calculated. Spectra simulated with a computer as well as data acquired with a video fluorometer are examined. Results indicate that all three parameters are sensitive to changes in peak position, peak width, relative peak height, and intensity of background noises.

EEG-Based Emotion Recognition Using Different Neural Network and Pattern Recognition Techniques A Review

2019 ◽  
Vol 7 (1) ◽  
pp. 615-618
Author(s):  
Y. M. Rajput ◽  
S. Abdul Hannan ◽  
M. Eid Alzahrani ◽  
Ramesh R. Manza ◽  
Dnyaneshwari D. Patil
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Emotion Recognition ◽  
Pattern Recognition Techniques

Gravity Models in International Trade: An Exploration in Econo-Physics

2021 ◽  
pp. 227797872198992
Author(s):  
Iman Pal ◽  
Saibal Kar
Keyword(s):  
Pattern Recognition ◽  
International Trade ◽  
Present Article ◽  
Gravity Models ◽  
Scientific Applications ◽  
Physical Sciences ◽  
Trade Patterns ◽  
Pattern Recognition Techniques ◽  
The Subject ◽  
Jel Classifications

Several strands of the static and dynamic theoretical constructs and the empirical applications in the subject of economics owe substantially to the well-known principles of physical sciences. The present article explores as to how the development of the popular gravity models in international trade can be traced back to Newton’s law of gravitation, and to both Ohm’s Law and Kirchhoff’s Law of current electricity, as well as to the pattern recognition techniques commonly deployed in scientific applications. In addition to surveying these theoretical analogies, the article also offers numerical applications for observed trade patterns between India and a set of countries. JEL Classifications: F41, F42, C61, F47

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