Description: Deep Learning Applications, Paperback by Wani, M. Arif (EDT); Raj, Bhiksha (EDT); Luo, Feng (EDT); Dou, Dejing (EDT), ISBN 9811633568, ISBN-13 9789811633560, Brand New, Free shipping in the US 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 th an essential reference guide for academic researchers, professionals, software engineers in the industry, and innovative product developers.
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Book Title: Deep Learning Applications
Number of Pages: Xii, 322 Pages
Publication Name: Deep Learning Applications, Volume 3
Language: English
Publisher: Springer
Publication Year: 2021
Subject: Engineering (General), Intelligence (Ai) & Semantics, Applied
Item Weight: 18.2 Oz
Type: Textbook
Item Length: 9.3 in
Author: Bhiksha Raj
Subject Area: Mathematics, Computers, Technology & Engineering
Item Width: 6.1 in
Series: Advances in Intelligent Systems and Computing Ser.
Format: Trade Paperback
