Deep Learning Applications In Computer Vision Signals And Networks

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Deep Learning Applications: In Computer Vision, Signals And Networks

Deep Learning Applications: In Computer Vision, Signals And Networks
Author :
Publisher : World Scientific
Total Pages : 309
Release :
ISBN-10 : 9789811266928
ISBN-13 : 9811266921
Rating : 4/5 (921 Downloads)

Book Synopsis Deep Learning Applications: In Computer Vision, Signals And Networks by : Qi Xuan

Download or read book Deep Learning Applications: In Computer Vision, Signals And Networks written by Qi Xuan and published by World Scientific. This book was released on 2023-03-21 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes various deep learning models featuring how deep learning algorithms have been applied and used in real-life settings. The complexity of real-world scenarios and constraints imposed by the environment, together with budgetary and resource limitations, have posed great challenges to engineers and developers alike, to come up with solutions to meet these demands. This book presents case studies undertaken by its contributors to overcome these problems. These studies can be used as references for designers when applying deep learning in solving real-world problems in the areas of vision, signals, and networks.The contents of this book are divided into three parts. In the first part, AI vision applications in plant disease diagnostics, PM2.5 concentration estimation, surface defect detection, and ship plate identification, are featured. The second part introduces deep learning applications in signal processing; such as time series classification, broad-learning based signal modulation recognition, and graph neural network (GNN) based modulation recognition. Finally, the last section of the book reports on graph embedding applications and GNN in AI for networks; such as an end-to-end graph embedding method for dispute detection, an autonomous System-GNN architecture to infer the relationship between Apache software, a Ponzi scheme detection framework to identify and detect Ponzi schemes, and a GNN application to predict molecular biological activities.


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