| 期刊全稱 | Advances in Applications of Data-Driven Computing | | 影響因子2023 | Jagdish Chand Bansal,Lance C. C. Fung,Ankush Ghosh | | 視頻video | http://file.papertrans.cn/147/146669/146669.mp4 | | 發(fā)行地址 | Discusses machine and deep learning approaches to data-driven applications.Provides original works presented at GUCON 2020.Serves as a reference for researchers and practitioners in academia and indus | | 學(xué)科分類 | Advances in Intelligent Systems and Computing | | 圖書封面 |  | | 影響因子 | .This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications. Applications of Artificial intelligence (AI)-based systems play a significant role in today’s software industry. The sensors data from hardware-based systems making a mammoth database, increasing day by day. Recent advances in big data generation and management have created an avenue for decision-makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioural modelling. As such, computational neural networks algorit | | Pindex | Book 2021 |
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