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portada Recent Advances in Deep Learning Applications. New Techniques and Practical Examples
Type
Physical Book
Year
2025
Pages
356
Format
Hardcover
Dimensions
23.40 x 15.60 cm
ISBN13
9781032944623

Recent Advances in Deep Learning Applications. New Techniques and Practical Examples

M. Arif Wani;Vasile Palade;Uche Onyekpe (Author) · Chapman & Hall/CRC · Hardcover

Recent Advances in Deep Learning Applications. New Techniques and Practical Examples - M. Arif Wani;Vasile Palade;Uche Onyekpe

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Synopsis "Recent Advances in Deep Learning Applications. New Techniques and Practical Examples"

This book presents a collection of extended papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023) and focuses on deep learning architectures and their applications in domains such as healthcare, security, education, fault diagnosis, and robotic control in industrial environments.

This book presents a collection of extended papers selected from the 22nd IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2023) and 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, large language models for the above applications are covered in this book. Readers will find insights to help them realize novel ways of using deep learning architectures and models in real-world applications and contexts, making the 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, software engineers in the industry, and innovative product developers.

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