LEADER 05196nam 22007095 450 001 9910483087803321 005 20251116224908.0 010 $a3-030-45529-7 024 7 $a10.1007/978-3-030-45529-3 035 $a(CKB)4100000011392474 035 $a(DE-He213)978-3-030-45529-3 035 $a(MiAaPQ)EBC6310351 035 $a(PPN)250216647 035 $a(EXLCZ)994100000011392474 100 $a20200818d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDomain Adaptation in Computer Vision with Deep Learning /$fedited by Hemanth Venkateswara, Sethuraman Panchanathan 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XI, 256 p. 76 illus., 55 illus. in color.) 311 08$a3-030-45528-9 320 $aIncludes bibliographical references. 327 $aPreface -- 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 Classi?er 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. 330 $aThis book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation. Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book. 606 $aMachine learning 606 $aOptical data processing 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aArtificial intelligence 606 $aApplication software 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputer Applications$3https://scigraph.springernature.com/ontologies/product-market-codes/I23001 615 0$aMachine learning. 615 0$aOptical data processing. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aArtificial intelligence. 615 0$aApplication software. 615 14$aMachine Learning. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aSignal, Image and Speech Processing. 615 24$aArtificial Intelligence. 615 24$aComputer Applications. 676 $a006.31 702 $aVenkateswara$b Hemanth$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPanchanathan$b Sethuraman$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483087803321 996 $aDomain Adaptation in Computer Vision with Deep Learning$92310999 997 $aUNINA