Public awareness of deep neural networks has exploded mainly because our planet is filled with predictive and analytical products in countless intelligent human-centered tools, including interpreters, targeted advertising, and prototyping intelligent transport systems. However, the underlying mechanisms allow these smart, human-centered products to remain obscure. By contrast, researchers from all fields incorporated deep neural networks into their experiments to solve problems that could not be solved before. In this chapter, we aim to thoroughly examine the applications and mechanisms of deep learning. We specifically aim to offer those who wish to know the depth of their understanding and its varied applications, classification in a range of smart world systems as a categorical compilation of the latest research. However, we also hope to develop fresh fields of study which include various kinds of deep learning.
CITATION STYLE
Niranjani, V., & Selvam, N. S. (2020). Overview on Deep Neural Networks: Architecture, Application and Rising Analysis Trends. In EAI/Springer Innovations in Communication and Computing (pp. 271–278). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-44407-5_18
Mendeley helps you to discover research relevant for your work.