Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

This article discusses how women have significant abilities to cope with the difficulties of war times. They are not the weak and vulnerable victims who are thought to be. On the contrary, they have the power to control over many-sided fronts, like participating in the battlefield as nurses or activists for peace, or even fighters, as well as through the tasks and responsibilities assigned to them to protect and support their families during wartime. The researcher will examine the impact of war upon women. Like men, women suffer during wartime. They are being injured, tortured and killed. Yet, they are able to give examples of love and courage even in the difficult times of war. Hana is one of those women who lived during wartimes,

In the present work, the image and representation of Adela, the youngest daughter of the family of the Casa de Bernarda Alba, one of the most popular works of the Spanish author Federico García Lorca (1898-1936), will be analyzed. In this work, there are different themes, but what concerns us is to show the repression, oppression and rebellion of this character in a context of customs of the 1920s in Spain. They are revealing elements in that period in which women were relegated to the background, despite the fact that a feminist movement had already begun in Spain. By studying Adela, we seek to see how a single woman confronts her family and the society that surrounds her to fight for freedom, although its end is finally linked to

Fingerprints are commonly utilized as a key technique and for personal recognition and in identification systems for personal security affairs. The most widely used fingerprint systems utilizing the distribution of minutiae points for fingerprint matching and representation. These techniques become unsuccessful when partial fingerprint images are capture, or the finger ridges suffer from lot of cuts or injuries or skin sickness. This paper suggests a fingerprint recognition technique which utilizes the local features for fingerprint representation and matching. The adopted local features have determined using Haar wavelet subbands. The system was tested experimentally using FVC2004 databases, which consists of four datasets, each set holds

This study deals with the orthographic processing ability of homophones which can account for variance in word recognition and production skills due to phonological processing. The study aims at: A )Investigating whether the students can recognize correct usage and spelling comprehension of different homophones by using appropriate word that overlapped in both phonology and orthography. B )Assessing spelling production word association to the written form of the homophone in the sentence comprehension task. To achieve these aims, two tests have been conducted and distributed on 50 students at first stage at the College of Education(Ibn-Rushd) for the academic year 2010-2011. The two tests are exposed to a jury of experts for the purpose of