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

The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

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

The design fabrics of the most important episodes that are at the core process rhetorical communication, until they became these episodes ample room for research and investigation, and the issue of non-familiar formality is nothing but the result of those relationships Constructivism, which is the result of an effort builders coherent activate the shape and attributes of phenotypic, therefore it will cause him a lot of questions about his and founded the organization in order to activate the speech communication between the product(cloth)and the receiver .On this basis, the research problem identified on imposing the question follows:1. Does the non-familiar formal role in enriching communication discourse of women's fabric designs?2. Ar

The method of measurement dosimetry in neutron – gamma field by using CaSo4 : Dy (PTFE) disc which has a diameter of 1.3mm and thickness of 0.2mm and using hydrogenated material as a converters of neutron to recoil protons (n-p) reaction, the discs were irradiated by neutron source (241Am-Be) with flux of 4.5?105 n/cm2s for different time to obtain different dose. The TL signals, which we have been obtained by using the converters, are increases to 71%. So we can resolve the neutron and gamma in mixed field.

In this research, we highlight the most important research related to the mixed ligand complexes of the drug trimethoprim (TMP), and for the past 7 years where this drug has been used as a chelating ligand and gives stability to the complexes with ions of metal elements where these complexes, prepared and diagnosed, and for some research the bacterial activity was studied against different types of bacteria