Titlebook: Deep Learning and Edge Computing Solutions for High Performance Computing; A. Suresh,Sara Paiva Book 2021 Springer Nature Switzerland AG 2

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Assessment as a Generative Dancel features from exudates digitally. The five-stage classification of the severity of the disease comprises of three stages of low risk and two stages of diabetic retinopathy. By implementing an automated system for identification of this disease we have a chance to accurately detect an affected pati

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2522-8595 e analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.978-3-030-60267-3978-3-030-60265-9Series ISSN 2522-8595 Series E-ISSN 2522-8609

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Deep Learning and Edge Computing Solutions for High Performance Computing

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Edge Computing: Next-Generation Computing,nts. Furthermore, the chapter explains the concept of edge computing and how it differs from cloud computing. In addition, typical layered architecture of the edge computing ecosystem is presented, and the various types of components present in each layer are outlined. The characteristics of edge co

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Deep Stack Neural Networks Based Learning Model for Fault Detection and Classification in Sensor Dating the temporal rationality of the data. Primary essence of the process is to diminish the cost function value. In order to acquire the minimal value the raw time series training data are levelheaded by the sensors. The next level is to scrutinize the classification accuracy of the Deep Stack Neur

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Fuzzy Adaptive Intelligent Controller for AC Servo Motor,n the Conventional fuzzy controller and conventional PD controller. For periodic reference tracking, the proposed controller exhibits a minimum Absolute Tracking Error (ATE) profile is the least with FAIC when compared to other controllers. The authors have also tested the robustness of the control