Wavelet Packet and Percent of Energy Distribution with Neural Networks Based Gender Identification System

Khalaf, Emad; Daqrouq, Khaled; Sherif, Mohamed Ahmed

doi:10.3923/jas.2011.2940.2946

Cited by 7 publications

(7 citation statements)

References 17 publications

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“…The results were interesting and showed that the more languages included, the better accuracy is obtained. In a more recent work on the same problem of gender identification, Khalaf et al [18] used wavelet packet transform (WPT) for extracting information from audio files. They applied Neural Network classifier on this extracted information.…”

Section: A Audio Classificationmentioning

confidence: 99%

Spoken Arabic dialects identification: The case of Egyptian and Jordanian dialects

Al‐Ayyoub

Rihani

Dalgamoni

et al. 2014

2014 5th International Conference on Information and Communication Systems (ICICS)

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Language identification systems have been the subject of extensive research efforts since the 1970's. Dialect identification is a natural extension of such systems. Most of the current systems do not consider the Arabic language and its dialects despite its immense importance. This paper addresses the problem of Arabic dialects identification. To the best of our knowledge, this is the first attempt to address this specific problem. Due to the lack of existing datasets, we collect our own dataset. To avoid collecting a prohibitively large dataset for the dozens of existing Arabic dialects, we focus on two specific dialects, viz. the Jordanian dialect and the Egyptian dialect. Several audio processing techniques (for feature extraction) and classifiers are tested to determine which combination of features/classifier generates the best results. Surprisingly, the results are very good.

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Section: A Audio Classificationmentioning

confidence: 99%

Spoken Arabic dialects identification: The case of Egyptian and Jordanian dialects

Al‐Ayyoub

Rihani

Dalgamoni

et al. 2014

2014 5th International Conference on Information and Communication Systems (ICICS)

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“…Este método en general, no es utilizado de forma directa, sino, como una etapa de preprocesado, para ser enviado por ejemplo a una red neuronal. Ejemplo de esto, en el estudio realizado en [13], por medio de reconocimiento de voz humana se pretende clasificar entre género masculino o femenino. Por otro lado, en [14], el propósito es la identificación de señales anormales en el cerebro, para determinar signos de epilepsia utilizando electroencefalograma (EEG).…”

Section: Retroalimentaciónunclassified

“…Aunque actualmente se utiliza la técnica de transformada de Fourier para realizar análisis y extracción de características en frecuencia, esta técnica genera un espacio de características del tamaño de la señal en el tiempo. En este documento, se utiliza una técnica basada en la transformada Wavelet para extraer características de la señal proveniente de la imaginación motora [13][14] [15]. La transformada Wavelet, muestra la relación que hay entre la onda objeto de análisis y un conjunto de ondas especiales con características peculiares de amplitud y frecuencias; el resultado final sería la suma de todos los valores obtenidos al variar las distintas características de dichas ondas.…”

Section: Retroalimentaciónunclassified

Caracterización de imaginación motora utilizando análisis de descomposición de bandas de energía

et al. 2019

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Este artículo trata sobre el análisis de las señales eléctricas generadas por el cerebro, cuando una persona imagina elmovimiento de sus extremidades superiores. Las señales que se estudian son adquiridas con un equipo de interfaz cerebro-computador y sonanalizadas utilizando la transformada Wavelet Discreta para la técnica de descomposición de banda de energía. El uso de esta técnica es novedosoen el análisis de las señales eléctricas generadas por el cerebro y los resultados que se obtuvieron indican que el uso de la técnica es factible parala caracterización de señales eléctricas provenientes del cerebro.

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“…For face recognition, wavelet decomposition with (PCA) [23], and Neural Networks [24] were presented. Wavelet transform as a tool also has been used for different tasks of recognition [25][26][27]. For more information about recognition tasks, reader can study other literature such as [28,29,30].…”

Section: Introductionmentioning

confidence: 99%

An Investigation of the Use of Eigen Values in Human Face Modeling for Recognition Tasks

Khalaf

2019

JAMCS

Self Cite

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The face image modeling by eigenvalues is not a new track in the literature. However, a much complete study is required to achieve a comprehensive investigation of the topic. In this research paper, an experimental methodology is conducted for studying the different alternatives of utilizing the eigenvalues for human face recognition. For a better universal investigation, three popular databases are tested; Orl_faces, extended Yale face_A, and extended Yale face_B datasets. The main objective of the study is to find the best choice of using eigenvalues (EV) in face recognition. The technique of the moving average filter (MAF) is combined with that of eigenvalues to enhance the results. Probabilistic neural network (PNN) is used for classification. Three methods of this concept were developed as follows: EV, EV with MAF, and MAF alone. The elapsed time was tested, where for moving average filter was distinctly smaller than the other two methods. For the Yaleface_B database, the eigenvalues method was superior for each of the three training/testing systems. The results were enhanced after using different filters instead of a direct moving average filter to make the proposed method the superior again. The study proved the possibility of using eigenvalues in conjunction with a suitable filter to get acceptable results for all types of image limitations. The concluded ideas elicited from the study spot the light on the usefulness of utilization of eigenvalues in the face recognition tasks.

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Wavelet Packet and Percent of Energy Distribution with Neural Networks Based Gender Identification System

Cited by 7 publications

References 17 publications

Spoken Arabic dialects identification: The case of Egyptian and Jordanian dialects

Spoken Arabic dialects identification: The case of Egyptian and Jordanian dialects

Caracterización de imaginación motora utilizando análisis de descomposición de bandas de energía

An Investigation of the Use of Eigen Values in Human Face Modeling for Recognition Tasks

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