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Genetic Neural Architecture Search for automatic assessment of human sperm images
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In: ISSN: 0957-4174 ; Expert Systems with Applications ; https://hal.archives-ouvertes.fr/hal-03585035 ; Expert Systems with Applications, Elsevier, 2022 (2022)
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| 2 |
Application of Modern Digital Systems and Approaches to Business Process Management
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In: Sustainability; Volume 14; Issue 3; Pages: 1697 (2022)
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| 3 |
Design and Development of a Genetic Algorithm Based on Fuzzy Inference Systems for Personnel Assignment Problem
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| 5 |
Term ranking adaptation to the domain: genetic algorithm based optimisation of the C-Value
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In: International Conference on Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-01972763 ; International Conference on Natural Language Processing, Springer, Jan 2014, Warsaw, Poland (2014)
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| 6 |
2005) Natural Language Syllable Alignment: From Conception to Implementation
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In: http://www.cs.mun.ca/~harold/Papers/NECEC05.pdf (2005)
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| 7 |
Data-Driven Generation of Compact, Accurate, and Linguistically-Sound Fuzzy Classifiers Based on a Decision-Tree Initialization
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In: http://www.fmt.vein.hu/softcomp/Abonyi02_dt2fm1.pdf (2002)
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| 8 |
Learning Phonology: Genetic Algorithms and Yoruba Tongue Root Harmony
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In: History Publications (2000)
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| 9 |
Self-Organizing and Genetic Algorithms for an Automatic Design of Fuzzy Control and Decision Systems
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In: http://ais.gmd.de/~surmann/papers/eufit93.pdf (1993)
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| 10 |
International Journal of Signal Processing, Image Processing and Pattern Recognition 55 Unstructured Document Categorization: A Study
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In: http://www.sersc.org/journals/IJSIP/vol1_no1/papers/07.pdf
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| 11 |
A Framework for Connected Speech Recognition for Thai Language*
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In: http://www.ist.cmu.ac.th/intech/paper/InTech0375.pdf
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| 12 |
Use of a Genetic Algorithm in Brill’s Transformation-Based Part-of-Speech Tagger
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In: http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005/docs/p2067.pdf
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| 13 |
Evolutionary Approach to Natural Language Word Sense Disambiguation through Global Coherence Optimization
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In: http://www.gelbukh.com/cv/Publications/2003/WSD-GA.pdf
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| 14 |
Sentence Prediction on SMS in Sinhala Language
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In: http://www.ijsrp.org/research-paper-1213/ijsrp-p2473.pdf
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| 15 |
GA and SVM V.Srinivasan
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In: http://research.ijcaonline.org/volume60/number2/pxc3884102.pdf
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Abstract:
The analysis of pathological voice is a challenging and an important area of research in speech processing. Acoustic characteristics of voice are used mainly to discriminate normal voices from pathological voices. This study explores methods to find the ability of acoustic parameters in discrimination of normal voices from pathological voices. An attempt is made to analyze and to classify pathological voice from normal voice in children. The classification of pathological voice from normal voice is implemented using support vector machine (SVM). The normal and pathological voices of children are used to train and test the classifier. A dataset is constructed by recording speech utterances of a set of Tamil phrases. The speech signal is then analyzed in order to extract the acoustic parameters such as the Signal Energy, pitch, formant frequencies, Mean Square Residual signal, Reflection coefficients, Jitter and Shimmer. In this study various acoustic features are combined to form a feature set, so as to detect voice disorders in children based on which further treatments can be prescribed by a pathologist. A Genetic Algorithm (GA) based feature selection is utilized to select best set of features which improves the classification accuracy.
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Keyword:
Feature Selection; Formants; General Terms Feature Extraction; Genetic Algorithm; Jitter; Pattern Classification Keywords Pitch; Reflection Coefficients; Shimmer; Signal Energy; SVM
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.303.4631
http://research.ijcaonline.org/volume60/number2/pxc3884102.pdf
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