scholarly journals Contextual Approach to Industrial Situation Recognition

TEM Journal ◽  
2020 ◽  
pp. 944-950
Author(s):  
V.N. Shepel` ◽  
N.V. Speshilova ◽  
V.A. Tripkosh ◽  
R.R. Rakhmatullin
Keyword(s):  
Recognition Algorithm ◽  
Management Systems ◽  
Context Information ◽  
Theory Method ◽  
Analysis Framework ◽  
Information Analysis ◽  
Recognition Error ◽  
Situation Recognition ◽  
Combination Theory ◽  
Recognition Systems

The article describes the development of multifaceted and efficient approaches to the context information analysis for synthesis of industrial situations context recognition algorithm in automated management systems within the enterprises. The probability theory method and method of statistical analysis, decision theory method, methods of algorithm and combination theory were used while researching. The research resulted in the development of new approaches to the context information analysis framework for pattern recognition which enables us to identify the procedure of contextual recognition for synthesis of working industrial situation recognition algorithm. A correspondence between the recognition error rate and the guaranteed recognition threshold, which can be used for setting up the automated context-based recognition systems, was analytically obtained during the research.

scholarly journals An Analysis Framework for the Evaluation of Content Management Systems

2006 ◽  
Vol 18 ◽  
Author(s):  
Claudio Vitari ◽  
Aurelio Ravarini ◽  
Florence Rodhain
Keyword(s):  
Content Management ◽  
Management Systems ◽  
Analysis Framework ◽  
Content Management Systems

Person Re-Identification Ranking Optimisation by Discriminant Context Information Analysis

2015 ◽  
Author(s):  
Jorge Garcia ◽  
Niki Martinel ◽  
Christian Micheloni ◽  
Alfredo Gardel
Keyword(s):  
Context Information ◽  
Information Analysis

scholarly journals Subsystem of Patent Information Analysis at the Stage of Conceptual Design of Management Systems Elements

2016 ◽  
Vol 101 ◽  
pp. 233-242
Author(s):  
Irina Petrova ◽  
Anna Puchkova ◽  
Viktoriya Zaripova
Keyword(s):  
Conceptual Design ◽  
Management Systems ◽  
Information Analysis ◽  
Patent Information

Iris Segmentation for Non-ideal Images

2015 ◽  
Vol 74 (3) ◽  
Author(s):  
Nasharuddin Zainal ◽  
Abduljalil Radman ◽  
Mahamod Ismail ◽  
Md Jan Nordin
Keyword(s):  
Iris Recognition ◽  
Recognition Algorithm ◽  
Segmentation Method ◽  
Iris Segmentation ◽  
West Virginia University ◽  
Segmentation Methods ◽  
Biometric Systems ◽  
Segmentation Algorithms ◽  
Recognition Systems ◽  
Constrained Conditions

Iris recognition has been regarded as one of the most reliable biometric systems over the past years. Previous studies have shown that the performance of iris recognition systems highly dependent on the performance of their segmentation algorithms. Iris segmentation is the process to isolate the iris region from the surrounded structures of the eye image. However, several iris segmentation algorithms have been developed in the literature, but their segmentation and recognition accuracies drastically degrade with non-ideal iris images acquired in less constrained conditions. Thus, it is crucial to develop a new iris segmentation method to improve iris recognition using non-ideal images. Hence, the objective of this paper is an iris segmentation method on the basis of optimization to isolate the iris region from non-ideal iris images such those affected by reflections, blurred boundaries, eyelids occlusion, and gaze-deviation. Experimental results on the off axis/angle West Virginia University (WVU) iris database demonstrated the superiority of the developed method over state-of-the-art iris segmentation methods considered in this paper. The performance of an iris recognition algorithm based on the developed iris segmentation method was observed to be improved.  

scholarly journals Automatic Roadblock Identification Algorithm for Unmanned Vehicles Based on Binocular Vision

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Liang Fang ◽  
Zhiwei Guan ◽  
Jinghua Li
Keyword(s):  
Coordinate System ◽  
Binocular Vision ◽  
Three Dimensional ◽  
Recognition Algorithm ◽  
Unmanned Vehicles ◽  
Identification Algorithm ◽  
Position Information ◽  
Recognition Error ◽  
Left And Right ◽  
Relative Position Information

In order to improve the accuracy of automatic obstacle recognition algorithm for driverless vehicles, an automatic obstacle recognition algorithm for driverless vehicles based on binocular vision is constructed. Firstly, the relevant parameters of the camera are calibrated around the new car coordinate system to determine the corresponding obstacle position of the vehicle. At the same time, the three-dimensional coordinates of obstacle points are obtained by binocular matching method. Then, the left and right cameras are used to capture the feature points of obstacles in the image to realize the recognition of obstacles. Finally, the experimental results show that for obstacle 1, the recognition error of the algorithm is 0.03 m; for obstacle 2, the recognition error is 0.02 m; for obstacle 3, the recognition error is 0.01 m. The algorithm has small recognition error. The vehicle coordinate system is added in the camera calibration process, which can accurately measure the relative position information between the vehicle and the obstacle.

scholarly journals On the Possibility of Embedding the Mechanism of Linguistic Anticipation into Speech Recognition Systems

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Daniel Kurushin ◽  
Natalia Nesterova ◽  
Olga Soboleva
Keyword(s):  
Speech Recognition ◽  
Human Brain ◽  
Recognition Algorithm ◽  
Learning Processes ◽  
Reading Technique ◽  
The Future ◽  
The Subject ◽  
Recognition Systems ◽  
Artificial Neural

The paper deals with the problems of modeling speech recognition systems. The authors proposed to use the mechanism of linguistic anticipation in the speech recognition systems. It is known that anticipation is a kind of phenomenon of anticipatory reflection, which can provide an opportunity for the subject to “look into the future.” Anticipation is believed to be an effective method of improving reading technique in children as it enables to increase the speed of reading [1]. The similarity of the learning processes of the human brain and artificial neural-like algorithms allows to suggest that the inclusion of anticipation mechanisms into the operation of the speech recognition algorithm can improve the quality of the system. The paper presents the experiment carried out with the purpose to study the probability of increasing the quality of modern speech recognition systems provided that linguistic anticipation is embedded into such a system. The obtained results are discussed and possible directions for further work on this topic are considered.

Application of 3D face recognition in the access control system

Robotica ◽  
2021 ◽  
pp. 1-19
Author(s):  
Quoc Dien Le ◽  
Tran Thanh Cong Vu ◽  
Tuong Quan Vo
Keyword(s):  
Control System ◽  
Face Recognition ◽  
Access Control ◽  
Facial Recognition ◽  
Recognition Algorithm ◽  
User Cooperation ◽  
Web Based ◽  
Access Control System ◽  
Recognition Systems ◽  
And Storage

Abstract Over the years, face recognition has been the research topic that has attracted many researchers around the world. One of the most significant applications of face recognition is the access control system. The access control system allows authorized persons to enter or exit certain or restricted areas. As a result, it will increase the security situation without over-investment in staff security. The access information can be the identification, time, and location, etc. It can be used to carry out human resource management tasks such as attendance and inspection of employees in a more fair and transparent manner. Although face recognition has been widely used in access control systems because of its better accuracy and convenience without requiring too much user cooperation, the 2D-based face recognition systems also retain many limitations due to the variations in pose and illumination. By analyzing facial geometries, 3D facial recognition systems can theoretically overcome the disadvantages of prior 2D methods and improve robustness in different working conditions. In this paper, we propose the 3D facial recognition algorithm for use in an access control system. The proposed algorithm includes the preprocessing, feature extraction, and classification stages. The application of the proposed access control system is the automatic sliding door, the controller of the system, the web-based monitoring, control, and storage of data.

A k-Nearest Neighbor Based Algorithm for Human Arm Movements Recognition Using EMG Signals

2010 ◽  
Vol 6 (2) ◽  
pp. 158-166
Author(s):  
Mohammed Al-Faiz ◽  
Abduladhem Ali ◽  
Abbas Miry
Keyword(s):  
Nearest Neighbor ◽  
Context Information ◽  
K Nearest Neighbor ◽  
Motion Classification ◽  
Multiple Parameters ◽  
Human Arm ◽  
Recognition Systems ◽  
Artificial Neural Network Ann ◽  
Human Arm Movements ◽  
Control Source

In a human–robot interface, the prediction of motion, which is based on context information of a task, has the potential to improve the robustness and reliability of motion classification to control human-assisting manipulators. The electromyography (EMG) signals can be used as a control source of artificial arm after it has been processed. The objective of this work is to achieve better classification with multiple parameters using KNearest Neighbor for different movements of a prosthetic arm. A K- Nearest Neighbor (K-NN) rule is one of the simplest and the most important methods in pattern recognition. The proposed structure is simulated using MATLAB Ver. R2009a, and satisfied results are obtained by comparing with conventional method of recognition using Artificial Neural Network(ANN), that explains the ability of the proposed structure to recognize the movements of human arm based EMG signals. Results show the proposed technique achieved a uniformly good performance with respect to ANN in term of time which is important in recognition systems, better accuracy in recognition when applied to lower SNR signal .

scholarly journals Interactive Evolution of Multidimensional Information in Social Media for Public Emergency: A Perspective from Optics Scattering

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaoyue Ma ◽  
Xiao Meng ◽  
Hao Ma
Keyword(s):  
Social Media ◽  
Interface Design ◽  
Theoretical Explanation ◽  
Context Information ◽  
Information Analysis ◽  
Practical Support ◽  
Multidimensional Information ◽  
Public Emergency ◽  
Information Components ◽  
The Impact

Abstract Most of the current research on the information analysis of social media (SM) for public emergency focused on a single dimension such as emotion while neglecting the interaction between multidimensional information. Therefore, in this study, an information dispersing–superimposing model is proposed to explain the implicit regularity of the impact within a symbol, sentiment, and context information and their dependent evolution on the SM. Information hue, saturation, and flux (HSF) are defined to measure the interaction process. An online event was selected to verify the concept and hypothesis of this study. The results proved that the interaction among multidimensional information did exist on the SM for a public emergency. The turning points of information dispersing–superimposing often emerged when the number of online users involved had significant changes, and sentiment and context information were showed to have a strong interaction relationship and tended to be spread at the same time. It was also manifested that the dominant information component was varied at each stage of the emergency. This paper is one of the first to study the interaction of multidimensional information on the SM derived from optics scattering. The findings of the study will try to provide a theoretical explanation for why certain information components may be enhanced during the online dissemination and suggest practical support for the information predictions and interface design for SM.

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