The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

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

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 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 question of word–formation motivation is one of the most urgent problems of morphological features of diminutive vocabulary in the languages of different structures, Arabic – Semitic and Russian - Slavic. The relevance of this question lies in the fact that the analysis of morphological elements of word-formation motivation plays an important role not only in identifying formal and semantic connections between different units of the same language, but also has an applied value in the comparative study of different languages. Taking in to account that word-formation motivation is usually considered sequentially in order to identify motivational relationships of this type of vocabulary, we will study motivation in comparative analy

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.