Informatics Publishing Limited

D. Dhayalan ¹, M. Yuvarani ¹, A. Nishanthi ¹, M. Sathiya ¹, T. Ranjani ¹

Affiliations
1 Department of MCA, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai - 600062, Tamil Nadu, IN

Abstract

Objective: In this paper, we deliver a concept based on image and video processing designs on behalf of eyesight else vision find out. Methods: The inducement of the study is for disabled people, without their hands. The vision checkup method is by using the mobile phone interaction. It utilizes the detected face location and vision detection is based on mobile phones for controlling eyelids state (close or open). Findings: This vision checkup method is used to show the improvement of accuracy of detection. In this mobile application, the light effect and the spaces among the disabled person eyes is tracking. The correctness of vision detection will be given by the usage of mobile devices. In existing, phone-based vision test for patients who wants to track their eyesight in their place itself, this type of gadgets could help to track people who are having defects in their eye before they lost more vision, and take the treatment in proposed this same tool could help the disabled persons also by using image processing of vision detection in eyelids state (close or open) detection. Improvements: The drawbacks are reduced in this proposed system. Finally, it provides the 99% of result for the complete detection of accurateness.

Keywords

Detection Accuracy, Eye Blink, Eye Checkup, Mobile Interaction, Vision Detection

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S. Ramasamy ¹, P.N. Periyasamy ¹, M. Sathiya ²

Affiliations
1 Department of Computer Science and Engineering, Hindusthan Institute of Technology, India., IN
2 Department of Information Technology, Karpagam Institute of Technology, India., IN

Abstract

This paper presents a resource allocation technique for industrial applications for 6G networks, which are characterised by the presence of many heterogeneous parameters that have an effect on the quality of data transmission. The purpose of the project is to achieve the greatest possible efficiency in the application of the resources that are presently while achieving a higher level of control over a diverse collection of sensing nodes operating within a hybrid network. The system model that has been proposed is a workable option for efficient resource allocation. The performance of the proposed method, in addition to similarities to the performance of other methods has been analysed. The proposed methods offer performance that is comparable to or better than the baseline, while simultaneously significantly reducing the SI exchange overhead and improving the system resilience to sensing intervals, some of which may be unavoidable in practise.

Keywords

ResNets, Resource Allocation, 6G, IoT.

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K. Karunambiga ¹, M. Sathiya ², S. Bhaggiaraj ³, K.C. Rajheshwari ⁴

Affiliations
1 Department of Computer Science and Engineering, Karpagam Institute of Technology, India., IN
2 Department of Information Technology, Karpagam Institute of Technology, India., IN
3 Department of Information Technology, Sri Ramakrishna Engineering College, India., IN
4 Department of Computer Science and Engineering, Sona College of Technology, India., IN

Abstract

In this paper, research develop a method for identifying abnormal behavior based on two inputs: the trustworthiness of the user, as well as the reliability of the recommendations that they make. Specifically, research look at the reliability of the user recommendations. The next thing that needs to be done is to calculate the node general trust value in order to determine if there has been any kind of malicious attack. This will show whether or not the node has been compromised in any way. It is conceivable that this could lessen the amount of power that is needed for the communication that takes place between different networks. Additionally, it demonstrates that the model is better able to utilize the evaluation results of the common neighbor nodes to synthesize the confidence value when fewer nodes are deployed in the network. This is demonstrated by the fact that fewer nodes are deployed in the network. The reliability of the trust assessment improves while the number of trusts for which recommendations are made decreases.

Keywords

Fuzzy Optimization, Trust, Score, MANETs, Direct Trust

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R. Jayadurga ¹, M. Sathiya ², G.K. Arpana ³

Affiliations
1 Department of Computer Science, Soundarya Institute of Management and Science, India., IN
2 Department of Information Technology, Karpagam Institute of Technology, India., IN
3 Department of Electronics and Communication Engineering, East West College of Engineering, India., IN

Abstract

Most of the time, these classifiers are trained using general-purpose datasets with a lot of classes. Therefore, the performance of these classifiers may not be as good as it could be. Both choosing classifiers based on registrations and dividing them into groups based on the subjects they cover are possible solutions that could lead to better classifier performance. This makes it clear that a classifier division and selection strategy needs for the proposed optimization to work. With the help of this method, the proposed model for feature extraction can choose an appropriate classifier while taking subscription constraints into account. There are subscriptions with the best values of n, and the results of using only n-class classifiers from one domain and ignoring classes from other domains are also given. These are in the same place as the effects of only using n-class classifiers from a certain domain. In this article, these are talked about in the same context as what happens when you only use n-class classifiers from a certain domain. For high-performance use of SAE-based systems, you need to use a classifier selection technique. This method is also needed for the investigation of multimedia events that need the method. To establish the effectiveness of the multimedia event-based system as well as its dependability, we are making use of traditional evaluation methods such as throughput and accuracy. These measures include the following: When compared to the efficiency of the system when using a classifier with a single class, the efficiency of the system diminishes as the number of classes per classifier increases. This is the case regardless of the other measures. This is the situation about both the throughput and the precision of the operation.

Keywords

Multimedia Data, Stacked Auto Encoder, Deep Learning, Classifier.

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M. Sathiya ¹, K. Karunambiga ², G. Sai Kumar ³, S. Chandra Sekaran ⁴

Affiliations
1 1Department of Information Technology, Karpagam Institute of Technology, India., IN
2 Department of Computer Science and Engineering, Karpagam Institute of Technology, India., IN
3 DVR and Dr. HS MIC College of Technology, India., IN
4 Department of Computer Science and Engineering, PSV College of Engineering and Technology, India., IN

Abstract

In recent years, there has been a meteoric rise in the application of deep neural networks for the purpose of iris segmentation. This can be attributed to the extraordinary capacity for learning possessed by the convolution kernels that are utilised by CNNs. Conventional methods have several drawbacks, some of which can be partially compensated for by using CNN-based algorithms, which increase the segmentation precision. On the other hand, the CNN-based iris segmentation approaches that are currently in use typically require a more complex network, which results in an increase in the number of parameters. This is essential to realise a higher degree of precision in the results. CNN-based techniques are effective, they can only be used for a specific application. This makes them inappropriate for general iris segmentation goals, even though they are effective.

Keywords

Ensemble Model, Deep Learning, Iris Segmentation.

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