Titlebook: Ubiquitous Intelligent Systems; Proceedings of ICUIS P. Karuppusamy,Isidoros Perikos,Fausto Pedro Garcí Conference proceedings 2022 The Edi

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A Deep Learning-Based Residual Network Model for Traffic Sign Detection and Classification,raffic signs from the real road scenes intensifies the safety of the intelligent vehicle systems. However, automatic detection and classification of traffic signs by such intelligent vehicle systems is a challenging task due to various factors such as variation in light illumination, different viewp

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A Survey on Energy-Efficient Approaches in Wireless Sensor Networks,sibilities. The areas of application of a WSN may vary from a small scale health-monitoring system (containing a few sensors) to a large scale soil-monitoring system (consisting of thousands of sensors). The deployment of the nodes of a WSN is generally done in hazardous, hostile or hard to reach en

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A Comparative Study on Augmented Analytics Using Deep Learning Techniques,et that belongs to a similar class as the novel image. In the area of image augmentation handling, a collection of operations is shifting, flipping, zooming, cropping, rotation, and transformation in color space. A wide range of applications frequently used the aspects of deep learning are industry,

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Performance Enhancement of Suspension System of an Electric Vehicle Using Nature Inspired Meta-Heurgral-derivative, and cascaded proportional-integral-proportional-derivative controller are tuned using a meta-heuristic based flower pollination algorithm to obtain the vehicle handling stability and control. Simulations using proposed algorithm are compared with other methods to showcase the effect

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Advancements in Healthcare: Multi-Agent Based Intelligent Sensor Approach,ing the literature and discussing applications using the technology in healthcare. The paper proposes a multi-agent system in a healthcare environment. It then conclude by discussing the merits and limitations of the technologies involved in the domain and their future scope.

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,Detection of Brain Tumors—A Comparative Analysis of Various Transfer Learning Methods,and treatment planning thus become highly important. Broadly, the methods used to diagnose tumors in the brain are computed tomography scan, magnetic resonance imaging scan and ultrasound imaging. Brain tumor detection is a crucial and difficult task in the medical image processing field, and it req