Deep Learning Applications, Volume 3 (1st ed. 2022) (Advances in Intelligent Systems and Computing #1395)

Synopsis

This book presents a compilation of extended version of selected papers from the 19th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2020) and focuses on deep learning networks in applications such as pneumonia detection in chest X-ray images, object detection and classification, RGB and depth image fusion, NLP tasks, dimensionality estimation, time series forecasting, building electric power grid for controllable energy resources, guiding charities in maximizing donations, and robotic control in industrial environments. Novel ways of using convolutional neural networks, recurrent neural network, autoencoder, deep evidential active learning, deep rapid class augmentation techniques, BERT models, multi-task learning networks, model compression and acceleration techniques, and conditional Feature Augmented and Transformed GAN (cFAT-GAN) 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 algorithms 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.

Copyright:

2022

Book Details

Book Quality:

Publisher Quality

ISBN-13:

9789811633577

Related ISBNs:

9789811633560

Publisher:

Springer Singapore, Singapore

Date of Addition:

11/12/21

Copyrighted By:

The Editor

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Computers and Internet, Technology, Mathematics and Statistics

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.

Edited by:

M. Arif Wani

Edited by:

Bhiksha Raj

Edited by:

Feng Luo

Edited by:

Dejing Dou