Recent Advances in Deep Learning Applications: New Techniques and Practical Examples
Authors: Onyekpe, U., Palade, V. and Wani, M.A.
Pages: 1-355
DOI: 10.1201/9781003570882
Abstract:This book presents a collection of rigorously revised papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023). It focuses on deep learning architectures and their applications in domains such as health care, security and threat detection, education, fault diagnosis, and robotic control in industrial environments. Novel ways of using convolutional neural networks, transformers, autoencoders, graph-based neural networks, and large language models for the above applications are covered in this book. Readers will fnd insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making this book an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers. Key Features: • Presents state-of-the-art research on deep learning • Covers modern real-world applications of deep learning • Provides value to students, academic researchers, professionals, softwareengineers in the industry, and innovative product developers.
Source: Scopus