menu
{ "item_title" : "Deep Learning Applications", "item_author" : [" Xuan Qi "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/81/126/690/9811266905_b.jpg", "price_data" : { "retail_price" : "109.00", "online_price" : "109.00", "our_price" : "109.00", "club_price" : "109.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Deep Learning Applications|Xuan Qi

Deep Learning Applications

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

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.

This item is Non-Returnable

Details

  • ISBN-13: 9789811266904
  • ISBN-10: 9811266905
  • Publisher: World Scientific Publishing Company
  • Publish Date: April 2023
  • Dimensions: 9 x 6 x 0.75 inches
  • Shipping Weight: 1.29 pounds
  • Page Count: 308

Related Categories

You May Also Like...

    1

BAM Customer Reviews