Biblio
Filters: Author is Anandhi, T. [Clear All Filters]
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2022. Facial Recognition System using Decision Tree Algorithm. 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC). :1542—1546.
Face recognition technology is widely employed in a variety of applications, including public security, criminal identification, multimedia data management, and so on. Because of its importance for practical applications and theoretical issues, the facial recognition system has received a lot of attention. Furthermore, numerous strategies have been offered, each of which has shown to be a significant benefit in the field of facial and pattern recognition systems. Face recognition still faces substantial hurdles in unrestricted situations, despite these advancements. Deep learning techniques for facial recognition are presented in this paper for accurate detection and identification of facial images. The primary goal of facial recognition is to recognize and validate facial features. The database consists of 500 color images of people that have been pre-processed and features extracted using Linear Discriminant Analysis. These features are split into 70 percent for training and 30 percent for testing of decision tree classifiers for the computation of face recognition system performance.
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2020. Energy Efficient Data Gathering Scheme in Underwater Sensor Networks. 2020 5th International Conference on Communication and Electronics Systems (ICCES). :480—485.
In this paper, an energy routing algorithm, called SAODV (secure Ad hoc On Demand Distance Vector) is designed for ad hoc mobile networks. SAODV is capable of both unicast and multicast routing. It is an on demand algorithm, meaning that it builds routes between nodes only as desired by source nodes. It maintains these routes as long as they are needed by the sources. Additionally, SAODV forms trees which connect multicast group members. The trees are composed of the group members and the nodes needed to connect the members. Extensive simulations are conducted to study the power consumption, the end-to-end delay, and the network throughput of our protocols compared with existing protocols. Efficiently handling losses in wireless environments, therefore, has significant importance. Even under benign conditions, various factors, like fading, interference, multi-path effects, and collisions, lead to heavy loss rates on wireless links.