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Generative Adversarial Learning: Architectures and Applications by Roozbeh Razav

Description: Generative Adversarial Learning: Architectures and Applications by Roozbeh Razavi-Far, Ariel Ruiz-Garcia, Vasile Palade, Juergen Schmidhuber Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Publisher Description This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs theoretical developments and their applications. Details ISBN 3030913899 ISBN-13 9783030913892 Title Generative Adversarial Learning: Architectures and Applications Author Roozbeh Razavi-Far, Ariel Ruiz-Garcia, Vasile Palade, Juergen Schmidhuber Format Hardcover Year 2022 Pages 355 Edition 1st Publisher Springer Nature Switzerland AG GE_Item_ID:137903839; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

Price: 218.25 USD

Location: Fairfield, Ohio

End Time: 2024-11-18T04:42:36.000Z

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Generative Adversarial Learning: Architectures and Applications by Roozbeh Razav

Item Specifics

Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money Back

ISBN-13: 9783030913892

Book Title: Generative Adversarial Learning: Architectures and Applications

Number of Pages: Xiv, 355 Pages

Language: English

Publication Name: Generative Adversarial Learning: Architectures and Applications

Publisher: Springer International Publishing A&G

Subject: Engineering (General), Intelligence (Ai) & Semantics, Probability & Statistics / General, General

Publication Year: 2022

Type: Textbook

Item Weight: 25.5 Oz

Author: Ariel Ruiz-Garcia

Subject Area: Mathematics, Computers, Technology & Engineering, Science

Item Length: 9.3 in

Item Width: 6.1 in

Series: Intelligent Systems Référence Library

Format: Hardcover

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