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Introduction to Domain Adaptation

In: Domain Adaptation in Computer Vision with Deep Learning

Author

Listed:
  • Hemanth Venkateswara

    (Arizona State University, Center for Cognitive Ubiquitous Computing (CUbiC), School of Computing Informatics and Decision Systems Engineering)

  • Sethuraman Panchanathan

    (Arizona State University, Center for Cognitive Ubiquitous Computing (CUbiC), School of Computing Informatics and Decision Systems Engineering)

Abstract

This chapter provides a formal introduction to transfer learning. We define transfer learning and provide examples of different forms of transfer learning in machine learning including domain adaptation. We outline different forms of domain adaptation and derive it’s performance bounds. The final section presents a brief description of the chapters in the book.

Suggested Citation

  • Hemanth Venkateswara & Sethuraman Panchanathan, 2020. "Introduction to Domain Adaptation," Springer Books, in: Hemanth Venkateswara & Sethuraman Panchanathan (ed.), Domain Adaptation in Computer Vision with Deep Learning, chapter 0, pages 3-21, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-45529-3_1
    DOI: 10.1007/978-3-030-45529-3_1
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