Domain adaptation in computer vision with deep learning. ([2020])

• Record Type: Book
• Further Information: Note: Edited by Hemanth Venkateswara, Sethuraman Panchanathan.
• Editors: Venkateswara, Hemanth; Panchanathan, Sethuraman
• Contents: Preface -- Part I: Introduction -- Chapter 1: Introduction to Domain Adaptation -- Chapter 2: Shallow Domain Adaptation -- Part II: Domain Alignment in the Feature Space -- Chapter 3: d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding -- Chapter 4: Deep Hashing Network for Unsupervised Domain Adaptation -- Chapter 5: Re-weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation -- Part III: Domain Alignment in the Image Space -- Chapter 6: Unsupervised Domain Adaptation with Duplex Generative Adversarial Network -- Chapter 7: Domain Adaptation via Image to Image Translation -- Chapter 8: Domain Adaptation via Image Style Transfer -- Part IV: Future Directions in Domain Adaptation -- Chapter 9: Towards Scalable Image Classifier Learning with Noisy Labels via Domain Adaptation -- Chapter 10: Adversarial Learning Approach for Open Set Domain Adaptation -- Chapter 11: Universal Domain Adaptation -- Chapter 12: Multi-source Domain Adaptation by Deep CockTail Networks -- Chapter 13: Zero-Shot Task Transfer.
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 006.31; Machine learning; Computer vision; Optical data processing; Signal processing; Image processing; Artificial intelligence; Electronic books
• Languages: English
• ISBNs: 9783030455293; 3030455297
• Related ISBNs: 9783030455286; 3030455289
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.