A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Filters
Recognition of similar objects using 2-D wavelet-fractal feature extraction
Object recognition supported by user interaction for service robots
Preserved Fulltext
Finally, an efficient and effective 2-D image fractal algorithm is used to extract each subband coefficient as a feature for classification. ...
A series of experiments were conducted on binary objects and character images for recognition and classification. ...
Introduction A flexible and reliable feature extraction method is one of most important factors for pattern recognition. ...
doi:10.1109/icpr.2002.1048303
dblp:conf/icpr/ZhangBS02
fatcat:wwabjxfiknbh7lc2vdijdiarlu
Identification of Partial Discharge Defects in Gas-Insulated Switchgears by Using a Deep Learning Method
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Traditional PD recognition methods are crucial for extracting features from PD patterns. The method of extracting crucial features is the key to PD pattern identification. ...
The fractal theory is commonly used to determine the features of discharge patterns. ...
Flowchart for the extraction of fractal features from PD patterns.
FIGURE 9 . 9 FIGURE 9. Fractal feature distribution extracted from 3D PD patterns.
FIGURE 11 . 11 FIGURE 11. ...
doi:10.1109/access.2020.3018553
fatcat:u3ow2ndzmzg5lc6peefgg4h7eu
Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors
2018
Royal Society Open Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Because of the limitations of the traditional fractal boxcounting dimension algorithm in subtle feature extraction of radiation source signals, a dual improved generalized fractal box-counting dimension ...
Finally, the dual improved fractal box-counting dimension eigenvectors formed the multi-dimensional eigenvectors as signal subtle features, which were used for radiation source signal recognition by the ...
Note: The approach of [23] is based on multifractal theory for extracting feature vectors and a GRA for achieving pattern recognition intelligently using the extracted feature vectors. ...
doi:10.1098/rsos.180087
pmid:29892447
pmcid:PMC5990805
fatcat:gu3mk3twbjhb7hhxfxhnwftxi4
The Improved Recognition Method of Radiation Signal under the Condition of Unstable SNR
2014
International Journal of Signal Processing, Image Processing and Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Firstly, it extracts box counting dimension features of four different radiation source signals, and then uses the characteristic values of stable box counting dimension as the inputs of the neural network ...
In order to solve this problem, in this paper, it proposes a radar signal recognition method based on fractal box dimension and neural network under the condition of unstable SNR. ...
Therefore, it will have good recognition results for radar signal feature extraction. ...
doi:10.14257/ijsip.2014.7.2.31
fatcat:ys4eb5r7zrh4limopxmjx45pfm
Signal Pattern Recognition Based on Fractal Features and Machine Learning
2018
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Fractal theory can be used for signal modulation feature extraction and recognition because of its good ability to express complex information. ...
Box fractal dimension, Katz fractal dimension, Higuchi fractal dimension, Petrosian fractal dimension, and Sevcik fractal dimension are extracted from eight different modulation signals for signal pattern ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app8081327
fatcat:7b3n7jm7hncrxegz5begsbclvq
Recognition of multiple partial discharge patterns by multi-class support vector machine using fractal image processing technique
2018
IET Science, Measurement & Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The extracted features used as the input vector for the classifiers for PD recognition. ...
In this proposed methodology, a combined algorithm of different edge detection methods with box-counting fractal image compression technique is used for fractal feature extraction. ...
and for permitting us to carry out this work in the High Voltage Engineering Laboratory of the institution. ...
doi:10.1049/iet-smt.2018.5020
fatcat:wdiakx4fuvb5faddy3g5mm6g2u
Fractal-based autonomous partial discharge pattern recognition method for MV motors
2018
High Voltage
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
C 2018, 'Fractal-based autonomous partial discharge pattern recognition method for MV motors ', IET High Voltage, vol. 3, no. 2, Abstract: On-line partial discharge (PD) monitoring is being increasingly ...
The main contributions include a polar PD (PPD) pattern and a fractal theory-based autonomous PD recognition method. ...
Then the fractal-based feature extraction is made to extract fractal dimension and lacunarity features from converted 3D PPD patterns. ...
doi:10.1049/hve.2017.0109
fatcat:qkmce6u6hbd6flgspu4jpjf7r4
Fractal Dimension Pattern Based Multiresolution Analysis for Rough Estimator of Person-Dependent Audio Emotion Recognition
[article]
2016
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Distinguish from other existing works, the person-dependent patterns of audio emotions are conducted, and fractal dimension features are calculated for acoustic feature extraction. ...
Furthermore, it is able to efficiently learn intrinsic characteristics of auditory emotions, while the utterance features are learned from fractal dimensions of each sub-bands. ...
solving the problem L (k) ∝ k −D . (4)
FRACTAL DIMENSION BASED AUDIO EMOTION RECOGNITION For an AER system, it is necessary to exploit the discriminative patterns with respect to chosen audio features ...
arXiv:1607.00087v2
fatcat:kakanc4wzvcvvkj3zt4yqj66za
Fractal dimension pattern-based multiresolution analysis for rough estimator of speaker-dependent audio emotion recognition
2017
International Journal of Wavelets, Multiresolution and Information Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Distinguish from other existing works, the person-dependent patterns of audio emotions are conducted, and fractal dimension features are calculated for acoustic feature extraction. ...
Furthermore, it is able to efficiently learn intrinsic characteristics of auditory emotions, while the utterance features are learned from fractal dimensions of each sub-bands. ...
solving the problem L (k) ∝ k −D . (4)
FRACTAL DIMENSION BASED AUDIO EMOTION RECOGNITION For an AER system, it is necessary to exploit the discriminative patterns with respect to chosen audio features ...
doi:10.1142/s0219691317500424
fatcat:xbnuxprilbcpzkql27etu7zb3a
An Improved Feature Extraction Algorithm of Radiation Source Based On Multiple Fractal Theory
2014
International Journal of Signal Processing, Image Processing and Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In the premise of simplified algorithm, the radar signal's multiple fractal dimensions we extract had better stability and lay a better foundation for the rest of the classifier recognition work. ...
In this paper, it proposes an improved feature extraction algorithm of radiation source signals based on the multiple fractal theory, it improves the solution method of traditional multiple fractal dimension ...
The fractal algorithm which has the best feature extraction results is the feature extraction algorithm based on the multi fractal dimension. ...
doi:10.14257/ijsip.2014.7.1.22
fatcat:ty5hpsxbhbgk5hvsjdqu6erowy
Face Recognition Using Nonlinear Feature Parameter and Artificial Neural Network
2010
International Journal of Computational Intelligence Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The paper reports a study of nonlinear nature of face image. A novel feature extraction method using state space feature parameter for the recognition of face images is studied. ...
Overall recognition accuracy obtained is better for ANN algorithm and is 98.5%. ...
In order to design high accuracy recognition system, the choice of feature extraction method is very crucial. ...
doi:10.2991/ijcis.2010.3.5.6
fatcat:grslo7zjavf7rpgqeg7k4ybmnm
Introduction of Fractal Based Information Processing and Recognition
2019
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Fractal characteristic, one typical nonlinear characteristic, is applied as a key characteristic in complex information processing and used in many research domains [...] ...
Acknowledgments: The guest editors are thankful to Takayoshi Kobayashi, Editor in Chief of Applied Sciences, as well as Assistant Editors of Applied Sciences for their supportive guidance during the entire ...
Conflicts of Interest: The authors declare no conflicts of interest. ...
doi:10.3390/app9071297
fatcat:yp56i32j2zaxvachkl24rrhbni
Application of T-S Fuzzy Neural Network to Pattern Recognition of Corona Discharge
2014
International Journal of Signal Processing, Image Processing and Pattern Recognition
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
this network, the structure is confirmed as the pattern recognition network in the types of corona discharge, and results show that the network is great effective for pattern recognition of corona discharge ...
In this paper,three types of corona discharge test model are designed, then characteristic signals of corona discharge, the maximum, minimum and mean value and including the fractal dimension, are extracted ...
subject (Research Fund of Heilongjiang Provincial Education Department No. 12511z008). ...
doi:10.14257/ijsip.2014.7.1.23
fatcat:rszhe6fi5vcxbdrnx6h2x4ipma
Font recognition using Variogram fractal dimension
2012
20th Iranian Conference on Electrical Engineering (ICEE2012)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
It considers font recognition as texture identification task and the extracted features are independent of document content. ...
The proposed method is based on one of the fractal dimension techniques which is called Variogram Analysis. ...
Feature Extraction Using Fractal Geometry Feature extraction is a crucial step in every pattern recognition system. ...
doi:10.1109/iraniancee.2012.6292432
fatcat:y6yumuwmsvgzfb75i7qdhaewca
The Pattern Recognition System Using the Fractal Dimension of Chaos Theory
2015
International Journal of Fuzzy Logic and Intelligent Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In this paper, we propose a method that extracts features from character patterns using the fractal dimension of chaos theory. The input character pattern image is converted into timeseries data. ...
Then, using the modified Henon system suggested in this paper, it determines the last features of the character pattern image after calculating the box-counting dimension, natural measure, information ...
Acknowledgements This work was supported by the 2015 Research Fund of Kimpo College, Korea. ...
doi:10.5391/ijfis.2015.15.2.121
fatcat:3ajitd5tvjgw5k6ypbwlcpmm5u
« Previous
Showing results 1 — 15 out of 10,414 results